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
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
The objective of this work is to model the microstructure of asphalt mixture and build virtual test for asphalt mixture by using Particle Flow Code in three dimensions(PFC^(3D))based on three-dimensional discrete elem...The objective of this work is to model the microstructure of asphalt mixture and build virtual test for asphalt mixture by using Particle Flow Code in three dimensions(PFC^(3D))based on three-dimensional discrete element method.A randomly generating algorithm was proposed to capture the three-dimensional irregular shape of coarse aggregate.And then,modeling algorithm and method for graded aggregates were built.Based on the combination of modeling of coarse aggregates,asphalt mastic and air voids,three-dimensional virtual sample of asphalt mixture was modeled by using PFC^(3D).Virtual tests for penetration test of aggregate and uniaxial creep test of asphalt mixture were built and conducted by using PFC^(3D).By comparison of the testing results between virtual tests and actual laboratory tests,the validity of the microstructure modeling and virtual test built in this study was verified.Additionally,compared with laboratory test,the virtual test is easier to conduct and has less variability.It is proved that microstructure modeling and virtual test based on three-dimensional discrete element method is a promising way to conduct research of asphalt mixture.展开更多
A modeling tool for simulating three-dimensional land frequency-domain controlled-source electromagnetic surveys,based on a finite-element discretization of the Helmholtz equation for the electric fields,has been deve...A modeling tool for simulating three-dimensional land frequency-domain controlled-source electromagnetic surveys,based on a finite-element discretization of the Helmholtz equation for the electric fields,has been developed.The main difference between our modeling method and those previous works is edge finite-element approach applied to solving the three-dimensional land frequency-domain electromagnetic responses generated by horizontal electric dipole source.Firstly,the edge finite-element equation is formulated through the Galerkin method based on Helmholtz equation of the electric fields.Secondly,in order to check the validity of the modeling code,the numerical results are compared with the analytical solutions for a homogeneous half-space model.Finally,other three models are simulated with three-dimensional electromagnetic responses.The results indicate that the method can be applied for solving three-dimensional electromagnetic responses.The algorithm has been demonstrated,which can be effective to modeling the complex geo-electrical structures.This efficient algorithm will help to study the distribution laws of3-D land frequency-domain controlled-source electromagnetic responses and to setup basis for research of three-dimensional inversion.展开更多
A finite element algorithm combined with divergence condition was presented for computing three-dimensional(3D) magnetotelluric forward modeling. The finite element equation of three-dimensional magnetotelluric forwar...A finite element algorithm combined with divergence condition was presented for computing three-dimensional(3D) magnetotelluric forward modeling. The finite element equation of three-dimensional magnetotelluric forward modeling was derived from Maxwell's equations using general variation principle. The divergence condition was added forcedly to the electric field boundary value problem, which made the solution correct. The system of equation of the finite element algorithm was a large sparse, banded, symmetric, ill-conditioned, non-Hermitian complex matrix equation, which can be solved using the Bi-CGSTAB method. In order to prove correctness of the three-dimensional magnetotelluric forward algorithm, the computed results and analytic results of one-dimensional geo-electrical model were compared. In addition, the three-dimensional magnetotelluric forward algorithm is given a further evaluation by computing COMMEMI model. The forward modeling results show that the algorithm is very efficient, and it has a lot of advantages, such as the high precision, the canonical process of solving problem, meeting the internal boundary condition automatically and adapting to all kinds of distribution of multi-substances.展开更多
The strategies that minimize the overall solution time of multiple linear systems in 3D finite element method (FEM) modeling of direct current (DC) resistivity were discussed. A global stiff matrix is assembled and st...The strategies that minimize the overall solution time of multiple linear systems in 3D finite element method (FEM) modeling of direct current (DC) resistivity were discussed. A global stiff matrix is assembled and stored in two parts separately. One part is associated with the volume integral and the other is associated with the subsurface boundary integral. The equivalent multiple linear systems with closer right-hand sides than the original systems were constructed. A recycling Krylov subspace technique was employed to solve the multiple linear systems. The solution of the seed system was used as an initial guess for the subsequent systems. The results of two numerical experiments show that the improved algorithm reduces the iterations and CPU time by almost 50%, compared with the classical preconditioned conjugate gradient method.展开更多
In this paper, the method based on uniform design and neural network is proposed to model the complex system. In order to express the system characteristics all round, uniform design method is used to choose the model...In this paper, the method based on uniform design and neural network is proposed to model the complex system. In order to express the system characteristics all round, uniform design method is used to choose the modeling samples and obtain the overall information of the system;for the purpose of modeling the system or its characteristics, the artificial neural network is used to construct the model. Experiment indicates that this method can model the complex system effectively.展开更多
In order to reflect the stochastic characteristics of structures more comprehensively and accurately, a theory and method for modeling of structures with stochastic parameters is presented by using probability finite ...In order to reflect the stochastic characteristics of structures more comprehensively and accurately, a theory and method for modeling of structures with stochastic parameters is presented by using probability finite element method and stochastic experiment data of structures based on the modeling of structures with deterministic parameters. Double-decker space frame is taken as an example to validate this theory and method, good results are gained.展开更多
To enhance the computational efficiency of spatio-temporally discretized phase-field models,we present a high-speed solver specifically designed for the Poisson equations,a component frequently used in the numerical c...To enhance the computational efficiency of spatio-temporally discretized phase-field models,we present a high-speed solver specifically designed for the Poisson equations,a component frequently used in the numerical computation of such models.This efficient solver employs algorithms based on discrete cosine transformations(DCT)or discrete sine transformations(DST)and is not restricted by any spatio-temporal schemes.Our proposed methodology is appropriate for a variety of phase-field models and is especially efficient when combined with flow field systems.Meanwhile,this study has conducted an extensive numerical comparison and found that employing DCT and DST techniques not only yields results comparable to those obtained via the Multigrid(MG)method,a conventional approach used in the resolution of the Poisson equations,but also enhances computational efficiency by over 90%.展开更多
In this paper,a linear optimization method(LOM)for the design of terahertz circuits is presented,aimed at enhancing the simulation efficacy and reducing the time of the circuit design workflow.This method enables the ...In this paper,a linear optimization method(LOM)for the design of terahertz circuits is presented,aimed at enhancing the simulation efficacy and reducing the time of the circuit design workflow.This method enables the rapid determination of optimal embedding impedance for diodes across a specific bandwidth to achieve maximum efficiency through harmonic balance simulations.By optimizing the linear matching circuit with the optimal embedding impedance,the method effectively segregates the simulation of the linear segments from the nonlinear segments in the frequency multiplier circuit,substantially improving the speed of simulations.The design of on-chip linear matching circuits adopts a modular circuit design strategy,incorporating fixed load resistors to simplify the matching challenge.Utilizing this approach,a 340 GHz frequency doubler was developed and measured.The results demonstrate that,across a bandwidth of 330 GHz to 342 GHz,the efficiency of the doubler remains above 10%,with an input power ranging from 98 mW to 141mW and an output power exceeding 13 mW.Notably,at an input power of 141 mW,a peak output power of 21.8 mW was achieved at 334 GHz,corresponding to an efficiency of 15.8%.展开更多
To address the problems of low accuracy by the CONWEP model and poor efficiency by the Coupled Eulerian-Lagrangian(CEL)method in predicting close-range air blast loads of cylindrical charges,a neural network-based sim...To address the problems of low accuracy by the CONWEP model and poor efficiency by the Coupled Eulerian-Lagrangian(CEL)method in predicting close-range air blast loads of cylindrical charges,a neural network-based simulation(NNS)method with higher accuracy and better efficiency was proposed.The NNS method consisted of three main steps.First,the parameters of blast loads,including the peak pressures and impulses of cylindrical charges with different aspect ratios(L/D)at different stand-off distances and incident angles were obtained by two-dimensional numerical simulations.Subsequently,incident shape factors of cylindrical charges with arbitrary aspect ratios were predicted by a neural network.Finally,reflected shape factors were derived and implemented into the subroutine of the ABAQUS code to modify the CONWEP model,including modifications of impulse and overpressure.The reliability of the proposed NNS method was verified by related experimental results.Remarkable accuracy improvement was acquired by the proposed NNS method compared with the unmodified CONWEP model.Moreover,huge efficiency superiority was obtained by the proposed NNS method compared with the CEL method.The proposed NNS method showed good accuracy when the scaled distance was greater than 0.2 m/kg^(1/3).It should be noted that there is no need to generate a new dataset again since the blast loads satisfy the similarity law,and the proposed NNS method can be directly used to simulate the blast loads generated by different cylindrical charges.The proposed NNS method with high efficiency and accuracy can be used as an effective method to analyze the dynamic response of structures under blast loads,and it has significant application prospects in designing protective structures.展开更多
This paper examined how microstructure influences the homogenized thermal conductivity of cellular structures and revealed a surface-induced size-dependent effect.This effect is linked to the porous microstructural fe...This paper examined how microstructure influences the homogenized thermal conductivity of cellular structures and revealed a surface-induced size-dependent effect.This effect is linked to the porous microstructural features of cellular structures,which stems from the degree of porosity and the distri-bution of the pores.Unlike the phonon-driven surface effect at the nanoscale,the macro-scale surface mechanism in thermal cellular structures is found to be the microstructure-induced changes in the heat conduction path based on fully resolved 3D numerical simulations.The surface region is determined by the microstructure,characterized by the intrinsic length.With the coupling between extrinsic and intrinsic length scales under the surface mechanism,a surface-enriched multiscale method was devel-oped to accurately capture the complex size-dependent thermal conductivity.The principle of scale separation required by classical multiscale methods is not necessary to be satisfied by the proposed multiscale method.The significant potential of the surface-enriched multiscale method was demon-strated through simulations of the effective thermal conductivity of a thin-walled metamaterial struc-ture.The surface-enriched multiscale method offers higher accuracy compared with the classical multiscale method and superior efficiency over high-fidelity finite element methods.展开更多
[Objective]Accurate prediction of tomato growth height is crucial for optimizing production environments in smart farming.However,current prediction methods predominantly rely on empirical,mechanistic,or learning-base...[Objective]Accurate prediction of tomato growth height is crucial for optimizing production environments in smart farming.However,current prediction methods predominantly rely on empirical,mechanistic,or learning-based models that utilize either images data or environmental data.These methods fail to fully leverage multi-modal data to capture the diverse aspects of plant growth comprehensively.[Methods]To address this limitation,a two-stage phenotypic feature extraction(PFE)model based on deep learning algorithm of recurrent neural network(RNN)and long short-term memory(LSTM)was developed.The model integrated environment and plant information to provide a holistic understanding of the growth process,emploied phenotypic and temporal feature extractors to comprehensively capture both types of features,enabled a deeper understanding of the interaction between tomato plants and their environment,ultimately leading to highly accurate predictions of growth height.[Results and Discussions]The experimental results showed the model's ef‐fectiveness:When predicting the next two days based on the past five days,the PFE-based RNN and LSTM models achieved mean absolute percentage error(MAPE)of 0.81%and 0.40%,respectively,which were significantly lower than the 8.00%MAPE of the large language model(LLM)and 6.72%MAPE of the Transformer-based model.In longer-term predictions,the 10-day prediction for 4 days ahead and the 30-day prediction for 12 days ahead,the PFE-RNN model continued to outperform the other two baseline models,with MAPE of 2.66%and 14.05%,respectively.[Conclusions]The proposed method,which leverages phenotypic-temporal collaboration,shows great potential for intelligent,data-driven management of tomato cultivation,making it a promising approach for enhancing the efficiency and precision of smart tomato planting management.展开更多
The capability requirements of the command, control, communication, computing, intelligence, surveillance, reconnaissance （C41SR） systems are full of uncertain and vague information, which makes it difficult to mode...The capability requirements of the command, control, communication, computing, intelligence, surveillance, reconnaissance （C41SR） systems are full of uncertain and vague information, which makes it difficult to model the C41SR architecture. The paper presents an approach to modeling the capability requirements with the fuzzy unified modeling language （UML） and building domain ontologies with fuzzy description logic （DL）. The UML modeling constructs are extended according to the meta model of Depart- ment of Defense Architecture Framework to improve their domain applicability, the fuzzy modeling mechanism is introduced to model the fuzzy efficiency features of capabilities, and the capability requirement models are converted into ontologies formalized in fuzzy DL so that the model consistency and reasonability can be checked with a DL reasoning system. Finally, a case study of C41SR capability requirements model checking is provided to demonstrate the availability and applicability of the method.展开更多
3D dynamic analysis models of 1000 m deep-ocean mining pipeline, including steel lift pipe, pump, buffer and flexible hose, were established by finite element method (FEM). The coupling effect of steel lift pipe and f...3D dynamic analysis models of 1000 m deep-ocean mining pipeline, including steel lift pipe, pump, buffer and flexible hose, were established by finite element method (FEM). The coupling effect of steel lift pipe and flexible hose, and main external loads of pipeline were considered in the models, such as gravity, buoyancy, hydrodynamic forces, internal and external fluid pressures, concentrated suspension buoyancy on the flexible hose, torsional moment and axial force induced by pump working. Some relevant FEM models and solution techniques were developed, according to various 3D transient behaviors of integrated deep-ocean mining pipeline, including towing motions of track-keeping operation and launch process of pipeline. Meanwhile, an experimental verification system in towing water tank that had similar characteristics of designed mining pipeline was developed to verify the accuracy of the FEM models and dynamic simulation. The experiment results show that the experimental records and simulation results of stress of pipe are coincided. Based on the further simulations of 1 000 m deep-ocean mining pipeline, the simulation results show that, to form configuration of a saddle shape, the total concentrated suspension buoyancy of flexible hose should be 95%?105% of the gravity of flexible hose in water, the first suspension point occupies 1/3 of the total buoyancy, and the second suspension point occupies 2/3 of the total buoyancy. When towing velocity of mining system is less than 0.5 m/s, the towing track of buffer is coincided with the setting route of ship on the whole and the configuration of flexible hose is also kept well.展开更多
In order to meet the demand of online optimal running, a novel soft sensor modeling approach based on Gaussian processes was proposed. The approach is moderately simple to implement and use without loss of performance...In order to meet the demand of online optimal running, a novel soft sensor modeling approach based on Gaussian processes was proposed. The approach is moderately simple to implement and use without loss of performance. It is trained by optimizing the hyperparameters using the scaled conjugate gradient algorithm with the squared exponential covariance function employed. Experimental simulations show that the soft sensor modeling approach has the advantage via a real-world example in a refinery. Meanwhile, the method opens new possibilities for application of kernel methods to potential fields.展开更多
The scattering centers(SCs)of low-detectable targets(LDTs)have a low scattering intensity.It is difficult to build the SC model of an LDT using the existing methods because these methods mainly concern dominant SCs wi...The scattering centers(SCs)of low-detectable targets(LDTs)have a low scattering intensity.It is difficult to build the SC model of an LDT using the existing methods because these methods mainly concern dominant SCs with strong scattering contributions.This paper presents an SC modeling approach to acquire the weak SCs of LDTs.We employ the induced currents at the LDT to search SCs,and the joint time-frequency transform together with the Hough transform to separate the scattering contributions of different SCs.Particle swarm optimization(PSO)is applied to improve the estimation results of SCs.The accuracy of the SC model built by this approach is verified by a full-wave numerical method.The validation results show that the SC model of the LDT can precisely simulate the signatures of high-resolution images,such as high-resolution range profile and inverse synthetic aperture radar(ISAR)images.展开更多
Nowadays an increasing number of workflow products and research prototypes begin to adopt XML for representing workflow models owing to its easy use and well understanding for people and machines. However, most of wor...Nowadays an increasing number of workflow products and research prototypes begin to adopt XML for representing workflow models owing to its easy use and well understanding for people and machines. However, most of workflow products and research prototypes provide the few supports for the verification of XML-based workflow model, such as free-deadlock properties, which is essential to successful application of workflow technology. In this paper, we tackle this problem by mapping the XML-based workflow model into Petri-net, a kind of well-known formalism for modeling, analyzing and verifying system. As a result, the XML-based workflow model can be automatically verified with the help of general Petri-net tools, such as DANAMICS. The presented approach not only enables end users to represent workflow model with XML-based modeling language, but also the correctness of model can be ensured, thus satisfying the needs of business processes.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.
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.
基金Project(51378006) supported by National Natural Science Foundation of ChinaProject(141076) supported by Huoyingdong Foundation of the Ministry of Education of China+1 种基金Project(2242015R30027) supported by Excellent Young Teacher Program of Southeast University,ChinaProject(BK20140109) supported by the Natural Science Foundation of Jiangsu Province,China
文摘The objective of this work is to model the microstructure of asphalt mixture and build virtual test for asphalt mixture by using Particle Flow Code in three dimensions(PFC^(3D))based on three-dimensional discrete element method.A randomly generating algorithm was proposed to capture the three-dimensional irregular shape of coarse aggregate.And then,modeling algorithm and method for graded aggregates were built.Based on the combination of modeling of coarse aggregates,asphalt mastic and air voids,three-dimensional virtual sample of asphalt mixture was modeled by using PFC^(3D).Virtual tests for penetration test of aggregate and uniaxial creep test of asphalt mixture were built and conducted by using PFC^(3D).By comparison of the testing results between virtual tests and actual laboratory tests,the validity of the microstructure modeling and virtual test built in this study was verified.Additionally,compared with laboratory test,the virtual test is easier to conduct and has less variability.It is proved that microstructure modeling and virtual test based on three-dimensional discrete element method is a promising way to conduct research of asphalt mixture.
基金Projects(41674080,41674079)supported by the National Natural Science Foundation of China
文摘A modeling tool for simulating three-dimensional land frequency-domain controlled-source electromagnetic surveys,based on a finite-element discretization of the Helmholtz equation for the electric fields,has been developed.The main difference between our modeling method and those previous works is edge finite-element approach applied to solving the three-dimensional land frequency-domain electromagnetic responses generated by horizontal electric dipole source.Firstly,the edge finite-element equation is formulated through the Galerkin method based on Helmholtz equation of the electric fields.Secondly,in order to check the validity of the modeling code,the numerical results are compared with the analytical solutions for a homogeneous half-space model.Finally,other three models are simulated with three-dimensional electromagnetic responses.The results indicate that the method can be applied for solving three-dimensional electromagnetic responses.The algorithm has been demonstrated,which can be effective to modeling the complex geo-electrical structures.This efficient algorithm will help to study the distribution laws of3-D land frequency-domain controlled-source electromagnetic responses and to setup basis for research of three-dimensional inversion.
基金Project(60672042) supported by the National Natural Science Foundation of China
文摘A finite element algorithm combined with divergence condition was presented for computing three-dimensional(3D) magnetotelluric forward modeling. The finite element equation of three-dimensional magnetotelluric forward modeling was derived from Maxwell's equations using general variation principle. The divergence condition was added forcedly to the electric field boundary value problem, which made the solution correct. The system of equation of the finite element algorithm was a large sparse, banded, symmetric, ill-conditioned, non-Hermitian complex matrix equation, which can be solved using the Bi-CGSTAB method. In order to prove correctness of the three-dimensional magnetotelluric forward algorithm, the computed results and analytic results of one-dimensional geo-electrical model were compared. In addition, the three-dimensional magnetotelluric forward algorithm is given a further evaluation by computing COMMEMI model. The forward modeling results show that the algorithm is very efficient, and it has a lot of advantages, such as the high precision, the canonical process of solving problem, meeting the internal boundary condition automatically and adapting to all kinds of distribution of multi-substances.
基金Projects(40974077,41164004)supported by the National Natural Science Foundation of ChinaProject(2007AA06Z134)supported by the National High Technology Research and Development Program of China+2 种基金Projects(2011GXNSFA018003,0832263)supported by the Natural Science Foundation of Guangxi Province,ChinaProject supported by Program for Excellent Talents in Guangxi Higher Education Institution,ChinaProject supported by the Foundation of Guilin University of Technology,China
文摘The strategies that minimize the overall solution time of multiple linear systems in 3D finite element method (FEM) modeling of direct current (DC) resistivity were discussed. A global stiff matrix is assembled and stored in two parts separately. One part is associated with the volume integral and the other is associated with the subsurface boundary integral. The equivalent multiple linear systems with closer right-hand sides than the original systems were constructed. A recycling Krylov subspace technique was employed to solve the multiple linear systems. The solution of the seed system was used as an initial guess for the subsequent systems. The results of two numerical experiments show that the improved algorithm reduces the iterations and CPU time by almost 50%, compared with the classical preconditioned conjugate gradient method.
文摘In this paper, the method based on uniform design and neural network is proposed to model the complex system. In order to express the system characteristics all round, uniform design method is used to choose the modeling samples and obtain the overall information of the system;for the purpose of modeling the system or its characteristics, the artificial neural network is used to construct the model. Experiment indicates that this method can model the complex system effectively.
基金the National Natural Science Foundation of China (5963140) Doctor Point Fund of National Education Committee Parent Company Fund of Aviation Industry
文摘In order to reflect the stochastic characteristics of structures more comprehensively and accurately, a theory and method for modeling of structures with stochastic parameters is presented by using probability finite element method and stochastic experiment data of structures based on the modeling of structures with deterministic parameters. Double-decker space frame is taken as an example to validate this theory and method, good results are gained.
基金Supported by Shanxi Province Natural Science Research(202203021212249)Special/Youth Foundation of Taiyuan University of Technology(2022QN101)+3 种基金National Natural Science Foundation of China(12301556)Research Project Supported by Shanxi Scholarship Council of China(2021-029)International Cooperation Base and Platform Project of Shanxi Province(202104041101019)Basic Research Plan of Shanxi Province(202203021211129)。
文摘To enhance the computational efficiency of spatio-temporally discretized phase-field models,we present a high-speed solver specifically designed for the Poisson equations,a component frequently used in the numerical computation of such models.This efficient solver employs algorithms based on discrete cosine transformations(DCT)or discrete sine transformations(DST)and is not restricted by any spatio-temporal schemes.Our proposed methodology is appropriate for a variety of phase-field models and is especially efficient when combined with flow field systems.Meanwhile,this study has conducted an extensive numerical comparison and found that employing DCT and DST techniques not only yields results comparable to those obtained via the Multigrid(MG)method,a conventional approach used in the resolution of the Poisson equations,but also enhances computational efficiency by over 90%.
基金Supported by the Beijing Municipal Science&Technology Commission(Z211100004421012),the Key Reaserch and Development Pro⁃gram of China(2022YFF0605902)。
文摘In this paper,a linear optimization method(LOM)for the design of terahertz circuits is presented,aimed at enhancing the simulation efficacy and reducing the time of the circuit design workflow.This method enables the rapid determination of optimal embedding impedance for diodes across a specific bandwidth to achieve maximum efficiency through harmonic balance simulations.By optimizing the linear matching circuit with the optimal embedding impedance,the method effectively segregates the simulation of the linear segments from the nonlinear segments in the frequency multiplier circuit,substantially improving the speed of simulations.The design of on-chip linear matching circuits adopts a modular circuit design strategy,incorporating fixed load resistors to simplify the matching challenge.Utilizing this approach,a 340 GHz frequency doubler was developed and measured.The results demonstrate that,across a bandwidth of 330 GHz to 342 GHz,the efficiency of the doubler remains above 10%,with an input power ranging from 98 mW to 141mW and an output power exceeding 13 mW.Notably,at an input power of 141 mW,a peak output power of 21.8 mW was achieved at 334 GHz,corresponding to an efficiency of 15.8%.
基金financially supported by the National Natural Science Foundation of China(Grant Nos.52271317 and 52071149)the Fundamental Research Funds for the Central Universities(HUST:2019kfy XJJS007)。
文摘To address the problems of low accuracy by the CONWEP model and poor efficiency by the Coupled Eulerian-Lagrangian(CEL)method in predicting close-range air blast loads of cylindrical charges,a neural network-based simulation(NNS)method with higher accuracy and better efficiency was proposed.The NNS method consisted of three main steps.First,the parameters of blast loads,including the peak pressures and impulses of cylindrical charges with different aspect ratios(L/D)at different stand-off distances and incident angles were obtained by two-dimensional numerical simulations.Subsequently,incident shape factors of cylindrical charges with arbitrary aspect ratios were predicted by a neural network.Finally,reflected shape factors were derived and implemented into the subroutine of the ABAQUS code to modify the CONWEP model,including modifications of impulse and overpressure.The reliability of the proposed NNS method was verified by related experimental results.Remarkable accuracy improvement was acquired by the proposed NNS method compared with the unmodified CONWEP model.Moreover,huge efficiency superiority was obtained by the proposed NNS method compared with the CEL method.The proposed NNS method showed good accuracy when the scaled distance was greater than 0.2 m/kg^(1/3).It should be noted that there is no need to generate a new dataset again since the blast loads satisfy the similarity law,and the proposed NNS method can be directly used to simulate the blast loads generated by different cylindrical charges.The proposed NNS method with high efficiency and accuracy can be used as an effective method to analyze the dynamic response of structures under blast loads,and it has significant application prospects in designing protective structures.
基金supported by the National Key Research and Development Program of China(Grant No.2021YFB1714600)the National Natural Science Foundation of China(Grant No.52175095)the Young Top-Notch Talent Cultivation Program of Hubei Province of China.
文摘This paper examined how microstructure influences the homogenized thermal conductivity of cellular structures and revealed a surface-induced size-dependent effect.This effect is linked to the porous microstructural features of cellular structures,which stems from the degree of porosity and the distri-bution of the pores.Unlike the phonon-driven surface effect at the nanoscale,the macro-scale surface mechanism in thermal cellular structures is found to be the microstructure-induced changes in the heat conduction path based on fully resolved 3D numerical simulations.The surface region is determined by the microstructure,characterized by the intrinsic length.With the coupling between extrinsic and intrinsic length scales under the surface mechanism,a surface-enriched multiscale method was devel-oped to accurately capture the complex size-dependent thermal conductivity.The principle of scale separation required by classical multiscale methods is not necessary to be satisfied by the proposed multiscale method.The significant potential of the surface-enriched multiscale method was demon-strated through simulations of the effective thermal conductivity of a thin-walled metamaterial struc-ture.The surface-enriched multiscale method offers higher accuracy compared with the classical multiscale method and superior efficiency over high-fidelity finite element methods.
文摘[Objective]Accurate prediction of tomato growth height is crucial for optimizing production environments in smart farming.However,current prediction methods predominantly rely on empirical,mechanistic,or learning-based models that utilize either images data or environmental data.These methods fail to fully leverage multi-modal data to capture the diverse aspects of plant growth comprehensively.[Methods]To address this limitation,a two-stage phenotypic feature extraction(PFE)model based on deep learning algorithm of recurrent neural network(RNN)and long short-term memory(LSTM)was developed.The model integrated environment and plant information to provide a holistic understanding of the growth process,emploied phenotypic and temporal feature extractors to comprehensively capture both types of features,enabled a deeper understanding of the interaction between tomato plants and their environment,ultimately leading to highly accurate predictions of growth height.[Results and Discussions]The experimental results showed the model's ef‐fectiveness:When predicting the next two days based on the past five days,the PFE-based RNN and LSTM models achieved mean absolute percentage error(MAPE)of 0.81%and 0.40%,respectively,which were significantly lower than the 8.00%MAPE of the large language model(LLM)and 6.72%MAPE of the Transformer-based model.In longer-term predictions,the 10-day prediction for 4 days ahead and the 30-day prediction for 12 days ahead,the PFE-RNN model continued to outperform the other two baseline models,with MAPE of 2.66%and 14.05%,respectively.[Conclusions]The proposed method,which leverages phenotypic-temporal collaboration,shows great potential for intelligent,data-driven management of tomato cultivation,making it a promising approach for enhancing the efficiency and precision of smart tomato planting management.
文摘The capability requirements of the command, control, communication, computing, intelligence, surveillance, reconnaissance （C41SR） systems are full of uncertain and vague information, which makes it difficult to model the C41SR architecture. The paper presents an approach to modeling the capability requirements with the fuzzy unified modeling language （UML） and building domain ontologies with fuzzy description logic （DL）. The UML modeling constructs are extended according to the meta model of Depart- ment of Defense Architecture Framework to improve their domain applicability, the fuzzy modeling mechanism is introduced to model the fuzzy efficiency features of capabilities, and the capability requirement models are converted into ontologies formalized in fuzzy DL so that the model consistency and reasonability can be checked with a DL reasoning system. Finally, a case study of C41SR capability requirements model checking is provided to demonstrate the availability and applicability of the method.
基金Project(DY105-3-2-2) supported by China Ocean Mineral Resources Research and Development Association(COMRA)Project(50675226) supported by the National Natural Science Foundation of China
文摘3D dynamic analysis models of 1000 m deep-ocean mining pipeline, including steel lift pipe, pump, buffer and flexible hose, were established by finite element method (FEM). The coupling effect of steel lift pipe and flexible hose, and main external loads of pipeline were considered in the models, such as gravity, buoyancy, hydrodynamic forces, internal and external fluid pressures, concentrated suspension buoyancy on the flexible hose, torsional moment and axial force induced by pump working. Some relevant FEM models and solution techniques were developed, according to various 3D transient behaviors of integrated deep-ocean mining pipeline, including towing motions of track-keeping operation and launch process of pipeline. Meanwhile, an experimental verification system in towing water tank that had similar characteristics of designed mining pipeline was developed to verify the accuracy of the FEM models and dynamic simulation. The experiment results show that the experimental records and simulation results of stress of pipe are coincided. Based on the further simulations of 1 000 m deep-ocean mining pipeline, the simulation results show that, to form configuration of a saddle shape, the total concentrated suspension buoyancy of flexible hose should be 95%?105% of the gravity of flexible hose in water, the first suspension point occupies 1/3 of the total buoyancy, and the second suspension point occupies 2/3 of the total buoyancy. When towing velocity of mining system is less than 0.5 m/s, the towing track of buffer is coincided with the setting route of ship on the whole and the configuration of flexible hose is also kept well.
文摘In order to meet the demand of online optimal running, a novel soft sensor modeling approach based on Gaussian processes was proposed. The approach is moderately simple to implement and use without loss of performance. It is trained by optimizing the hyperparameters using the scaled conjugate gradient algorithm with the squared exponential covariance function employed. Experimental simulations show that the soft sensor modeling approach has the advantage via a real-world example in a refinery. Meanwhile, the method opens new possibilities for application of kernel methods to potential fields.
基金This work was supported by the National Key R&D Program of China(2017YFB0202500)the National Natural Science Foundation of China(61771052).
文摘The scattering centers(SCs)of low-detectable targets(LDTs)have a low scattering intensity.It is difficult to build the SC model of an LDT using the existing methods because these methods mainly concern dominant SCs with strong scattering contributions.This paper presents an SC modeling approach to acquire the weak SCs of LDTs.We employ the induced currents at the LDT to search SCs,and the joint time-frequency transform together with the Hough transform to separate the scattering contributions of different SCs.Particle swarm optimization(PSO)is applied to improve the estimation results of SCs.The accuracy of the SC model built by this approach is verified by a full-wave numerical method.The validation results show that the SC model of the LDT can precisely simulate the signatures of high-resolution images,such as high-resolution range profile and inverse synthetic aperture radar(ISAR)images.
文摘Nowadays an increasing number of workflow products and research prototypes begin to adopt XML for representing workflow models owing to its easy use and well understanding for people and machines. However, most of workflow products and research prototypes provide the few supports for the verification of XML-based workflow model, such as free-deadlock properties, which is essential to successful application of workflow technology. In this paper, we tackle this problem by mapping the XML-based workflow model into Petri-net, a kind of well-known formalism for modeling, analyzing and verifying system. As a result, the XML-based workflow model can be automatically verified with the help of general Petri-net tools, such as DANAMICS. The presented approach not only enables end users to represent workflow model with XML-based modeling language, but also the correctness of model can be ensured, thus satisfying the needs of business processes.
