Hyperparameter tuning is a key step in developing high-performing machine learning models, but searching large hyperparameter spaces requires extensive computation using standard sequential methods. This work analyzes...Hyperparameter tuning is a key step in developing high-performing machine learning models, but searching large hyperparameter spaces requires extensive computation using standard sequential methods. This work analyzes the performance gains from parallel versus sequential hyperparameter optimization. Using scikit-learn’s Randomized SearchCV, this project tuned a Random Forest classifier for fake news detection via randomized grid search. Setting n_jobs to -1 enabled full parallelization across CPU cores. Results show the parallel implementation achieved over 5× faster CPU times and 3× faster total run times compared to sequential tuning. However, test accuracy slightly dropped from 99.26% sequentially to 99.15% with parallelism, indicating a trade-off between evaluation efficiency and model performance. Still, the significant computational gains allow more extensive hyperparameter exploration within reasonable timeframes, outweighing the small accuracy decrease. Further analysis could better quantify this trade-off across different models, tuning techniques, tasks, and hardware.展开更多
It is important to calculate the reachable domain(RD)of the manned lunar mission to evaluate whether a lunar landing site could be reached by the spacecraft. In this paper, the RD of free return orbits is quickly eval...It is important to calculate the reachable domain(RD)of the manned lunar mission to evaluate whether a lunar landing site could be reached by the spacecraft. In this paper, the RD of free return orbits is quickly evaluated and calculated via the classification and regression neural networks. An efficient databasegeneration method is developed for obtaining eight types of free return orbits and then the RD is defined by the orbit’s inclination and right ascension of ascending node(RAAN) at the perilune. A classify neural network and a regression network are trained respectively. The former is built for classifying the type of the RD, and the latter is built for calculating the inclination and RAAN of the RD. The simulation results show that two neural networks are well trained. The classification model has an accuracy of more than 99% and the mean square error of the regression model is less than 0.01°on the test set. Moreover, a serial strategy is proposed to combine the two surrogate models and a recognition tool is built to evaluate whether a lunar site could be reached. The proposed deep learning method shows the superiority in computation efficiency compared with the traditional double two-body model.展开更多
The constant bubble size modeling approach(CBSM)and variable bubble size modeling approach(VBSM)are frequently employed in Eulerian–Eulerian simulation of bubble columns.However,the accuracy of CBSM is limited while ...The constant bubble size modeling approach(CBSM)and variable bubble size modeling approach(VBSM)are frequently employed in Eulerian–Eulerian simulation of bubble columns.However,the accuracy of CBSM is limited while the computational efficiency of VBSM needs to be improved.This work aims to develop method for bubble size modeling which has high computational efficiency and accuracy in the simulation of bubble columns.The distribution of bubble sizes is represented by a series of discrete points,and the percentage of bubbles with various sizes at gas inlet is determined by the results of computational fluid dynamics(CFD)–population balance model(PBM)simulations,whereas the influence of bubble coalescence and breakup is neglected.The simulated results of a 0.15 m diameter bubble column suggest that the developed method has high computational speed and can achieve similar accuracy as CFD–PBM modeling.Furthermore,the convergence issues caused by solving population balance equations are addressed.展开更多
This paper presents a novel approximating method to construct highprecision single-patch representation of B-spline surface from a multi-patch representation for isogeometric applications.In isogeometric analysis,mult...This paper presents a novel approximating method to construct highprecision single-patch representation of B-spline surface from a multi-patch representation for isogeometric applications.In isogeometric analysis,multi-patch structure is not easy to achieve high continuity between neighboring patches which will reduce the advantage of isogeometric analysis in a sense.The proposed method can achieve high continuity at surface stitching region with low geometric error,and this technique exploits constructing the approximate surface with several control points are from original surfaces,which guarantees the local feature of the surface can be well-preserved with high precision.With the proposed approximating method,isogeometric analysis results using the new single-patch can be obtained efficiently compared with the original multi-patch structure.Several examples are presented to illustrate the effectiveness,accuracy and efficiency of the proposed method.展开更多
Construction of high-order difference schemes based on Taylor series expansion has long been a hot topic in computational mathematics, while its application in comprehensive weather models is still very rare. Here, th...Construction of high-order difference schemes based on Taylor series expansion has long been a hot topic in computational mathematics, while its application in comprehensive weather models is still very rare. Here, the properties of high-order finite difference schemes are studied based on idealized numerical testing, for the purpose of their application in the Global/Regional Assimilation and Prediction System(GRAPES) model. It is found that the pros and cons due to grid staggering choices diminish with higher-order schemes based on linearized analysis of the one-dimensional gravity wave equation. The improvement of higher-order difference schemes is still obvious for the mesh with smooth varied grid distance. The results of discontinuous square wave testing also exhibits the superiority of high-order schemes. For a model grid with severe non-uniformity and non-orthogonality, the advantage of high-order difference schemes is inapparent, as shown by the results of two-dimensional idealized advection tests under a terrain-following coordinate. In addition, the increase in computational expense caused by high-order schemes can be avoided by the precondition technique used in the GRAPES model. In general, a high-order finite difference scheme is a preferable choice for the tropical regional GRAPES model with a quasi-uniform and quasi-orthogonal grid mesh.展开更多
Relative dispersion ratio(RDR)can be used to quantify the deviation behavior of a water parcel’s trajectory caused by a disturbance in a hydrodynamic system.It can be calculated by using a standard method for determi...Relative dispersion ratio(RDR)can be used to quantify the deviation behavior of a water parcel’s trajectory caused by a disturbance in a hydrodynamic system.It can be calculated by using a standard method for determining relative dispersion(RD),which accounts for the growth of the deviation of a cluster of particles from a specific initial time.However,the standard method for computing RD is time consuming.It involves numerous computations on tracing many water parcels.In this study,a new method based on the adjoint method is proposed to acquire a series of RDR fields in one round of tracing.Through this method,the continuous variation in the RDR corresponding to a time series of the disturbance time t can be obtained.The consistency and efficiency of the new method are compared with those of the standard method by applying it to a double-gyre flow and an unsteady Arnold-Beltrami-Childress flow field.Results show that the two methods have good consistency in a finite time span.The new method has a notable speedup for evaluating the RDR at multiple t.展开更多
This work investigates the machining temperatures of ultra-fine-grained titanium(UFG Ti),prepared by equal channel angular extrusion,through analytical modeling.UFG Ti has great usefulness in biomedical applications b...This work investigates the machining temperatures of ultra-fine-grained titanium(UFG Ti),prepared by equal channel angular extrusion,through analytical modeling.UFG Ti has great usefulness in biomedical applications because of its high mechanical strength,sufficient manufacturability,and high biocompatibility.The temperatures were predicted using a physics-based predictive model based on material constitutive relation and mechanics of the orthogonal cutting process.The minimization between the stress calculated using Johnson–Cook constitutive model and the same stress calculated using mechanics model yields the estimation of machining temperatures at two deformation zones.Good agreements are observed upon validation to the values reported in the literature.The machinability of UFG Ti is investigated by comparing its machining temperature to that of Ti–6Al–4V alloy under the same cutting conditions.Significantly lower temperatures are observed in machining UFG Ti.The computational efficiency of the presented model is investigated by comparing its average computational time(~0.5 s)to that of a widely used modified chip formation model(8900 s)with comparable prediction accuracy.This work extends the applicability of the presented temperature model to a broader class of materials,specifically ultra-fine-grained metals.The high computational efficiency allows the in situ temperature prediction and optimization of temperature condition with process parameters planning.展开更多
In this article,we construct the most powerful family of simultaneous iterative method with global convergence behavior among all the existing methods in literature for finding all roots of non-linear equations.Conver...In this article,we construct the most powerful family of simultaneous iterative method with global convergence behavior among all the existing methods in literature for finding all roots of non-linear equations.Convergence analysis proved that the order of convergence of the family of derivative free simultaneous iterative method is nine.Our main aim is to check out the most regularly used simultaneous iterative methods for finding all roots of non-linear equations by studying their dynamical planes,numerical experiments and CPU time-methodology.Dynamical planes of iterative methods are drawn by using MATLAB for the comparison of global convergence properties of simultaneous iterative methods.Convergence behavior of the higher order simultaneous iterative methods are also illustrated by residual graph obtained from some numerical test examples.Numerical test examples,dynamical behavior and computational efficiency are provided to present the performance and dominant efficiency of the newly constructed derivative free family of simultaneous iterative method over existing higher order simultaneous methods in literature.展开更多
The standard lattice Boltzmann method utilizes uniform grids to maintain a compact computational procedure. However, it is often less efficient to perform hydrodynamic and aerodynamic flow simulations when there is a ...The standard lattice Boltzmann method utilizes uniform grids to maintain a compact computational procedure. However, it is often less efficient to perform hydrodynamic and aerodynamic flow simulations when there is a need for high resolution. To resolve these difficulties, a multiple nested lattice Boltzmann method(MNLBM) was developed, which contains several overlapped layers with different resolutions in the computational domain. The data transference of flow field on two layers is accomplished by a Filippova procedure which is proved to satisfy the continuity of mass, momentum, and stresses across the interface. The proposed method is based on the standard lattice Boltzmann method, so it is easily performed.By numerical investigation, the result of present method has been agreed with that of literature, but the computation efficiency is higher than the standard lattice Boltzmann method.展开更多
In order to investigate the applicability and performance of the Lattice Boltzmann Method( LBM) and the Monte Carlo Method( MCM) to simulate phonon heat transfer,a problem of phonon heat transfer in square geometry st...In order to investigate the applicability and performance of the Lattice Boltzmann Method( LBM) and the Monte Carlo Method( MCM) to simulate phonon heat transfer,a problem of phonon heat transfer in square geometry structures of silicon dioxide was taken as an example to compare the calculational results and analyze computational efficiency of the two methods. Moreover,this work analyzed the numerical stability for two methods. The results indicate that the MCM takes much more computation time than the LBM in the same condition. In addition,the results of the two methods have a good agreement in diffusive and diffusive-ballistic domain for investigating the phonon heat transfer. So they can be used to verify each other when the experiments of energy transport in these domains faces difficulty. In ballistic domain,duo to the random error,the temperature distribution curve from MCM is fluctuant.展开更多
This work illustrates the application of the “Second Order Comprehensive Adjoint Sensitivity Analysis Methodology” (2<sup>nd</sup>-CASAM) to a mathematical model that can simulate the evolution and/or tr...This work illustrates the application of the “Second Order Comprehensive Adjoint Sensitivity Analysis Methodology” (2<sup>nd</sup>-CASAM) to a mathematical model that can simulate the evolution and/or transmission of particles in a heterogeneous medium. The model response is the value of the model’s state function (particle concentration or particle flux) at a point in phase-space, which would simulate a pointwise measurement of the respective state function. This paradigm model admits exact closed-form expressions for all of the 1<sup>st</sup>- and 2<sup>nd</sup>-order response sensitivities to the model’s uncertain parameters and domain boundaries. These closed-form expressions can be used to verify the numerical results of production and/or commercial software, e.g., particle transport codes. Furthermore, this paradigm model comprises many uncertain parameters which have relative sensitivities of identical magnitudes. Therefore, this paradigm model could serve as a stringent benchmark for inter-comparing the performances of all deterministic and statistical sensitivity analysis methods, including the 2<sup>nd</sup>-CASAM.展开更多
This work continues the illustrative application of the “Second Order Comprehensive Adjoint Sensitivity Analysis Methodology” (2<sup>nd</sup>-CASAM) to a benchmark mathematical model that can simulate th...This work continues the illustrative application of the “Second Order Comprehensive Adjoint Sensitivity Analysis Methodology” (2<sup>nd</sup>-CASAM) to a benchmark mathematical model that can simulate the evolution and/or transmission of particles in a heterogeneous medium. The model response considered in this work is a reaction-rate detector response, which provides the average interactions of particles with the respective detector or, alternatively, the time-average of the concentration of a mixture of substances in a medium. The definition of this model response includes both uncertain boundary points of the benchmark, thereby providing both direct and indirect contributions to the response sensitivities stemming from the boundaries. The exact expressions for the 1<sup>st</sup>- and 2<sup>nd</sup>-order response sensitivities to the boundary and model parameters obtained in this work can serve as stringent benchmarks for inter-comparing the performances of all (deterministic and statistical) sensitivity analysis methods.展开更多
The use of high-fidelity Discrete Element Method(DEM)coupled with Computational Fluid Dynamics(CFD)for particle-scale simulations demands extensive simulation times and restricts application to small particulate syste...The use of high-fidelity Discrete Element Method(DEM)coupled with Computational Fluid Dynamics(CFD)for particle-scale simulations demands extensive simulation times and restricts application to small particulate systems.DEM-CFD simulations require good performance and satisfactory scalability on high-performance computing platforms.A reliable parallel computing strategy must be developed to calculate the collision forces,since collisions can occur between particles that are not on the same processor,or even across processors whose domains are disjoint.The present paper describes a parallelization technique and a numerical verification study based on a number of tests that allow for the assessment of the numerical performance of DEM used in conjunction with Large-Eddy Simulation(LES)to model dense flows in fluidized beds.The fluid phase is computed through solving the volume-averaged four-way coupling Navier-Stokes equations,in which the Smagorinsky sub-grid scale tensor model is used.Furthermore,the performance of Sub-Grid Scale(SGS)turbulence models applied to Fluidized Bed Reactor(FBR)configurations has been assessed and compared.The developed numerical solver represents an interesting combination of techniques that work well for the present purpose of studying particle formation in fluidized beds.展开更多
The background numerical noise#0 is determined by the maximum of truncation error and round-off error.For a chaotic system,the numerical error#(t)grows exponentially,say,#(t)=#0exp(kt),where k>0 is the so-called no...The background numerical noise#0 is determined by the maximum of truncation error and round-off error.For a chaotic system,the numerical error#(t)grows exponentially,say,#(t)=#0exp(kt),where k>0 is the so-called noise-growing exponent.This is the reason why one can not gain a convergent simulation of chaotic systems in a long enough interval of time by means of traditional algorithms in double precision,since the background numerical noise#0 might stop decreasing because of the use of double precision.This restriction can be overcome by means of the clean numerical simulation(CNS),which can decrease the background numerical noise#0 to any required tiny level.A lot of successful applications show the novelty and validity of the CNS.In this paper,we further propose some strategies to greatly increase the computational efficiency of the CNS algorithms for chaotic dynamical systems.It is highly suggested to keep a balance between truncation error and round-off error and besides to progressively enlarge the background numerical noise#0,since the exponentially increasing numerical noise#(t)is much larger than it.Some examples are given to illustrate the validity of our strategies for the CNS.展开更多
A promising way to boost popularity of electric vehicles(EVs)is to properly layout fast charging stations(FCSs)by jointly considering interactions among EV drivers,power systems and traffic network constraints.This pa...A promising way to boost popularity of electric vehicles(EVs)is to properly layout fast charging stations(FCSs)by jointly considering interactions among EV drivers,power systems and traffic network constraints.This paper proposes a novel sensitivity analysis-based FCS planning approach,which considers the voltage sensitivity of each sub-network in the distribution network and charging service availability for EV drivers in the transportation network.In addition,energy storage systems are optimally installed to provide voltage regulation service and enhance charging capacity.Simulation tests conducted on two distribution network and transportation network coupled systems validate the efficacy of the proposed approach.Moreover,comparison studies demonstrate the proposed approach outperforms a Voronoi graph and particle swarm optimization combined planning approach in terms of much higher computation efficiency.展开更多
Sequence-based protein tertiary structure prediction is of fundamental importance because the function of a protein ultimately depends on its 3 D structure.An accurate residue-residue contact map is one of the essenti...Sequence-based protein tertiary structure prediction is of fundamental importance because the function of a protein ultimately depends on its 3 D structure.An accurate residue-residue contact map is one of the essential elements for current ab initio prediction protocols of 3 D structure prediction.Recently,with the combination of deep learning and direct coupling techniques,the performance of residue contact prediction has achieved significant progress.However,a considerable number of current Deep-Learning(DL)-based prediction methods are usually time-consuming,mainly because they rely on different categories of data types and third-party programs.In this research,we transformed the complex biological problem into a pure computational problem through statistics and artificial intelligence.We have accordingly proposed a feature extraction method to obtain various categories of statistical information from only the multi-sequence alignment,followed by training a DL model for residue-residue contact prediction based on the massive statistical information.The proposed method is robust in terms of different test sets,showed high reliability on model confidence score,could obtain high computational efficiency and achieve comparable prediction precisions with DL methods that relying on multi-source inputs.展开更多
In this paper,we propose an approach to nucleon-pair approximation(NPA)with m-scheme bases,in which the collective nucleon pairs are represented in terms of antisymmetric matrices,and commutations between nucleon pair...In this paper,we propose an approach to nucleon-pair approximation(NPA)with m-scheme bases,in which the collective nucleon pairs are represented in terms of antisymmetric matrices,and commutations between nucleon pairs are given using a matrix multiplication that avoids angular-momentum couplings and recouplings.Therefore the present approach significantly simplifies the NPA computation.Furthermore,it is formulated on the same footing with and without isospin.展开更多
In order to model the dispersal of volcanic particles in the atmosphere and their deposition on the ground,one has to simulate an advection-diffusionsedimentation process on a large spatial area.Here we compare a Latt...In order to model the dispersal of volcanic particles in the atmosphere and their deposition on the ground,one has to simulate an advection-diffusionsedimentation process on a large spatial area.Here we compare a Lattice Boltzmann and a Cellular Automata approach.Our results show that for high Peclet regimes,the cellular automata model produce results that are as accurate as the lattice Boltzmann model and is computationally more effective.展开更多
文摘Hyperparameter tuning is a key step in developing high-performing machine learning models, but searching large hyperparameter spaces requires extensive computation using standard sequential methods. This work analyzes the performance gains from parallel versus sequential hyperparameter optimization. Using scikit-learn’s Randomized SearchCV, this project tuned a Random Forest classifier for fake news detection via randomized grid search. Setting n_jobs to -1 enabled full parallelization across CPU cores. Results show the parallel implementation achieved over 5× faster CPU times and 3× faster total run times compared to sequential tuning. However, test accuracy slightly dropped from 99.26% sequentially to 99.15% with parallelism, indicating a trade-off between evaluation efficiency and model performance. Still, the significant computational gains allow more extensive hyperparameter exploration within reasonable timeframes, outweighing the small accuracy decrease. Further analysis could better quantify this trade-off across different models, tuning techniques, tasks, and hardware.
基金supported by the National Natural Science Foundation of China (12072365)the Natural Science Foundation of Hunan Province of China (2020JJ4657)。
文摘It is important to calculate the reachable domain(RD)of the manned lunar mission to evaluate whether a lunar landing site could be reached by the spacecraft. In this paper, the RD of free return orbits is quickly evaluated and calculated via the classification and regression neural networks. An efficient databasegeneration method is developed for obtaining eight types of free return orbits and then the RD is defined by the orbit’s inclination and right ascension of ascending node(RAAN) at the perilune. A classify neural network and a regression network are trained respectively. The former is built for classifying the type of the RD, and the latter is built for calculating the inclination and RAAN of the RD. The simulation results show that two neural networks are well trained. The classification model has an accuracy of more than 99% and the mean square error of the regression model is less than 0.01°on the test set. Moreover, a serial strategy is proposed to combine the two surrogate models and a recognition tool is built to evaluate whether a lunar site could be reached. The proposed deep learning method shows the superiority in computation efficiency compared with the traditional double two-body model.
基金the National Natural Science Foundation of China(21625603)for supporting this work。
文摘The constant bubble size modeling approach(CBSM)and variable bubble size modeling approach(VBSM)are frequently employed in Eulerian–Eulerian simulation of bubble columns.However,the accuracy of CBSM is limited while the computational efficiency of VBSM needs to be improved.This work aims to develop method for bubble size modeling which has high computational efficiency and accuracy in the simulation of bubble columns.The distribution of bubble sizes is represented by a series of discrete points,and the percentage of bubbles with various sizes at gas inlet is determined by the results of computational fluid dynamics(CFD)–population balance model(PBM)simulations,whereas the influence of bubble coalescence and breakup is neglected.The simulated results of a 0.15 m diameter bubble column suggest that the developed method has high computational speed and can achieve similar accuracy as CFD–PBM modeling.Furthermore,the convergence issues caused by solving population balance equations are addressed.
基金This research was supported by the National Nature Science Foundation of China under Grant Nos.61602138,61772163 and 61761136010the NSFC-Zhejiang Joint Fund for the Integration of Industrialization and Informatization(Grant No.U1909210)Zhejiang Provincial Science and Technology Program in China(2018C01030).
文摘This paper presents a novel approximating method to construct highprecision single-patch representation of B-spline surface from a multi-patch representation for isogeometric applications.In isogeometric analysis,multi-patch structure is not easy to achieve high continuity between neighboring patches which will reduce the advantage of isogeometric analysis in a sense.The proposed method can achieve high continuity at surface stitching region with low geometric error,and this technique exploits constructing the approximate surface with several control points are from original surfaces,which guarantees the local feature of the surface can be well-preserved with high precision.With the proposed approximating method,isogeometric analysis results using the new single-patch can be obtained efficiently compared with the original multi-patch structure.Several examples are presented to illustrate the effectiveness,accuracy and efficiency of the proposed method.
基金supported by the National Natural Science Foundation of China (Grant No. U1811464)。
文摘Construction of high-order difference schemes based on Taylor series expansion has long been a hot topic in computational mathematics, while its application in comprehensive weather models is still very rare. Here, the properties of high-order finite difference schemes are studied based on idealized numerical testing, for the purpose of their application in the Global/Regional Assimilation and Prediction System(GRAPES) model. It is found that the pros and cons due to grid staggering choices diminish with higher-order schemes based on linearized analysis of the one-dimensional gravity wave equation. The improvement of higher-order difference schemes is still obvious for the mesh with smooth varied grid distance. The results of discontinuous square wave testing also exhibits the superiority of high-order schemes. For a model grid with severe non-uniformity and non-orthogonality, the advantage of high-order difference schemes is inapparent, as shown by the results of two-dimensional idealized advection tests under a terrain-following coordinate. In addition, the increase in computational expense caused by high-order schemes can be avoided by the precondition technique used in the GRAPES model. In general, a high-order finite difference scheme is a preferable choice for the tropical regional GRAPES model with a quasi-uniform and quasi-orthogonal grid mesh.
文摘Relative dispersion ratio(RDR)can be used to quantify the deviation behavior of a water parcel’s trajectory caused by a disturbance in a hydrodynamic system.It can be calculated by using a standard method for determining relative dispersion(RD),which accounts for the growth of the deviation of a cluster of particles from a specific initial time.However,the standard method for computing RD is time consuming.It involves numerous computations on tracing many water parcels.In this study,a new method based on the adjoint method is proposed to acquire a series of RDR fields in one round of tracing.Through this method,the continuous variation in the RDR corresponding to a time series of the disturbance time t can be obtained.The consistency and efficiency of the new method are compared with those of the standard method by applying it to a double-gyre flow and an unsteady Arnold-Beltrami-Childress flow field.Results show that the two methods have good consistency in a finite time span.The new method has a notable speedup for evaluating the RDR at multiple t.
文摘This work investigates the machining temperatures of ultra-fine-grained titanium(UFG Ti),prepared by equal channel angular extrusion,through analytical modeling.UFG Ti has great usefulness in biomedical applications because of its high mechanical strength,sufficient manufacturability,and high biocompatibility.The temperatures were predicted using a physics-based predictive model based on material constitutive relation and mechanics of the orthogonal cutting process.The minimization between the stress calculated using Johnson–Cook constitutive model and the same stress calculated using mechanics model yields the estimation of machining temperatures at two deformation zones.Good agreements are observed upon validation to the values reported in the literature.The machinability of UFG Ti is investigated by comparing its machining temperature to that of Ti–6Al–4V alloy under the same cutting conditions.Significantly lower temperatures are observed in machining UFG Ti.The computational efficiency of the presented model is investigated by comparing its average computational time(~0.5 s)to that of a widely used modified chip formation model(8900 s)with comparable prediction accuracy.This work extends the applicability of the presented temperature model to a broader class of materials,specifically ultra-fine-grained metals.The high computational efficiency allows the in situ temperature prediction and optimization of temperature condition with process parameters planning.
基金the Natural Science Foundation of China(Grant Nos.61673169,11301127,11701176,11626101,and 11601485)The Natural Science Foundation of Huzhou City(Grant No.2018YZ07).
文摘In this article,we construct the most powerful family of simultaneous iterative method with global convergence behavior among all the existing methods in literature for finding all roots of non-linear equations.Convergence analysis proved that the order of convergence of the family of derivative free simultaneous iterative method is nine.Our main aim is to check out the most regularly used simultaneous iterative methods for finding all roots of non-linear equations by studying their dynamical planes,numerical experiments and CPU time-methodology.Dynamical planes of iterative methods are drawn by using MATLAB for the comparison of global convergence properties of simultaneous iterative methods.Convergence behavior of the higher order simultaneous iterative methods are also illustrated by residual graph obtained from some numerical test examples.Numerical test examples,dynamical behavior and computational efficiency are provided to present the performance and dominant efficiency of the newly constructed derivative free family of simultaneous iterative method over existing higher order simultaneous methods in literature.
文摘The standard lattice Boltzmann method utilizes uniform grids to maintain a compact computational procedure. However, it is often less efficient to perform hydrodynamic and aerodynamic flow simulations when there is a need for high resolution. To resolve these difficulties, a multiple nested lattice Boltzmann method(MNLBM) was developed, which contains several overlapped layers with different resolutions in the computational domain. The data transference of flow field on two layers is accomplished by a Filippova procedure which is proved to satisfy the continuity of mass, momentum, and stresses across the interface. The proposed method is based on the standard lattice Boltzmann method, so it is easily performed.By numerical investigation, the result of present method has been agreed with that of literature, but the computation efficiency is higher than the standard lattice Boltzmann method.
基金Sponsored by the National Natural Science Foundation of China(Grant No.51176038)the Foundation for Innovative Research Groups of the National Natural Science Foundation of China(Grant No.51121004)
文摘In order to investigate the applicability and performance of the Lattice Boltzmann Method( LBM) and the Monte Carlo Method( MCM) to simulate phonon heat transfer,a problem of phonon heat transfer in square geometry structures of silicon dioxide was taken as an example to compare the calculational results and analyze computational efficiency of the two methods. Moreover,this work analyzed the numerical stability for two methods. The results indicate that the MCM takes much more computation time than the LBM in the same condition. In addition,the results of the two methods have a good agreement in diffusive and diffusive-ballistic domain for investigating the phonon heat transfer. So they can be used to verify each other when the experiments of energy transport in these domains faces difficulty. In ballistic domain,duo to the random error,the temperature distribution curve from MCM is fluctuant.
文摘This work illustrates the application of the “Second Order Comprehensive Adjoint Sensitivity Analysis Methodology” (2<sup>nd</sup>-CASAM) to a mathematical model that can simulate the evolution and/or transmission of particles in a heterogeneous medium. The model response is the value of the model’s state function (particle concentration or particle flux) at a point in phase-space, which would simulate a pointwise measurement of the respective state function. This paradigm model admits exact closed-form expressions for all of the 1<sup>st</sup>- and 2<sup>nd</sup>-order response sensitivities to the model’s uncertain parameters and domain boundaries. These closed-form expressions can be used to verify the numerical results of production and/or commercial software, e.g., particle transport codes. Furthermore, this paradigm model comprises many uncertain parameters which have relative sensitivities of identical magnitudes. Therefore, this paradigm model could serve as a stringent benchmark for inter-comparing the performances of all deterministic and statistical sensitivity analysis methods, including the 2<sup>nd</sup>-CASAM.
文摘This work continues the illustrative application of the “Second Order Comprehensive Adjoint Sensitivity Analysis Methodology” (2<sup>nd</sup>-CASAM) to a benchmark mathematical model that can simulate the evolution and/or transmission of particles in a heterogeneous medium. The model response considered in this work is a reaction-rate detector response, which provides the average interactions of particles with the respective detector or, alternatively, the time-average of the concentration of a mixture of substances in a medium. The definition of this model response includes both uncertain boundary points of the benchmark, thereby providing both direct and indirect contributions to the response sensitivities stemming from the boundaries. The exact expressions for the 1<sup>st</sup>- and 2<sup>nd</sup>-order response sensitivities to the boundary and model parameters obtained in this work can serve as stringent benchmarks for inter-comparing the performances of all (deterministic and statistical) sensitivity analysis methods.
基金supported by the National Natural Science Foundation of China (Grant No.11972309)Overseas Expertise Introduction Project for Discipline Innovation (the 111 Project) (Grant No.BP0719007).
文摘The use of high-fidelity Discrete Element Method(DEM)coupled with Computational Fluid Dynamics(CFD)for particle-scale simulations demands extensive simulation times and restricts application to small particulate systems.DEM-CFD simulations require good performance and satisfactory scalability on high-performance computing platforms.A reliable parallel computing strategy must be developed to calculate the collision forces,since collisions can occur between particles that are not on the same processor,or even across processors whose domains are disjoint.The present paper describes a parallelization technique and a numerical verification study based on a number of tests that allow for the assessment of the numerical performance of DEM used in conjunction with Large-Eddy Simulation(LES)to model dense flows in fluidized beds.The fluid phase is computed through solving the volume-averaged four-way coupling Navier-Stokes equations,in which the Smagorinsky sub-grid scale tensor model is used.Furthermore,the performance of Sub-Grid Scale(SGS)turbulence models applied to Fluidized Bed Reactor(FBR)configurations has been assessed and compared.The developed numerical solver represents an interesting combination of techniques that work well for the present purpose of studying particle formation in fluidized beds.
基金supported by National Natural Science Foundation of China(No.12272230)Shanghai Pilot Program for Basic Research-Shanghai Jiao Tong University(No.21TQ1400202).
文摘The background numerical noise#0 is determined by the maximum of truncation error and round-off error.For a chaotic system,the numerical error#(t)grows exponentially,say,#(t)=#0exp(kt),where k>0 is the so-called noise-growing exponent.This is the reason why one can not gain a convergent simulation of chaotic systems in a long enough interval of time by means of traditional algorithms in double precision,since the background numerical noise#0 might stop decreasing because of the use of double precision.This restriction can be overcome by means of the clean numerical simulation(CNS),which can decrease the background numerical noise#0 to any required tiny level.A lot of successful applications show the novelty and validity of the CNS.In this paper,we further propose some strategies to greatly increase the computational efficiency of the CNS algorithms for chaotic dynamical systems.It is highly suggested to keep a balance between truncation error and round-off error and besides to progressively enlarge the background numerical noise#0,since the exponentially increasing numerical noise#(t)is much larger than it.Some examples are given to illustrate the validity of our strategies for the CNS.
基金supported by the Science and Technology Project of State Grid Corporation of China(5108-202119040A-0-0-00).
文摘A promising way to boost popularity of electric vehicles(EVs)is to properly layout fast charging stations(FCSs)by jointly considering interactions among EV drivers,power systems and traffic network constraints.This paper proposes a novel sensitivity analysis-based FCS planning approach,which considers the voltage sensitivity of each sub-network in the distribution network and charging service availability for EV drivers in the transportation network.In addition,energy storage systems are optimally installed to provide voltage regulation service and enhance charging capacity.Simulation tests conducted on two distribution network and transportation network coupled systems validate the efficacy of the proposed approach.Moreover,comparison studies demonstrate the proposed approach outperforms a Voronoi graph and particle swarm optimization combined planning approach in terms of much higher computation efficiency.
基金supported by the Strategic Priority CAS Project (No. XDB38050100)the National Key Research and Development Program of China (No. 2018YFB0204403)+4 种基金the National Natural Science Foundation of China (No. U1813203)the Shenzhen Basic Research Fund (Nos. RCYX2020071411473419,JCYJ20200109114818703,and JSGG20201102163800001)CAS Key Lab (No. 2011DP173015)Hong Kong Research Grant Council (No. GRF-17208019)the Outstanding Youth Innovation Fund (Doctoral Students) of CAS-SIAT (No. Y9G054)。
文摘Sequence-based protein tertiary structure prediction is of fundamental importance because the function of a protein ultimately depends on its 3 D structure.An accurate residue-residue contact map is one of the essential elements for current ab initio prediction protocols of 3 D structure prediction.Recently,with the combination of deep learning and direct coupling techniques,the performance of residue contact prediction has achieved significant progress.However,a considerable number of current Deep-Learning(DL)-based prediction methods are usually time-consuming,mainly because they rely on different categories of data types and third-party programs.In this research,we transformed the complex biological problem into a pure computational problem through statistics and artificial intelligence.We have accordingly proposed a feature extraction method to obtain various categories of statistical information from only the multi-sequence alignment,followed by training a DL model for residue-residue contact prediction based on the massive statistical information.The proposed method is robust in terms of different test sets,showed high reliability on model confidence score,could obtain high computational efficiency and achieve comparable prediction precisions with DL methods that relying on multi-source inputs.
基金the Sichuan Science and Technology Program(2019JDRC0017)Doctoral Program of Southwest University of Science and Technology(18zx7147)+4 种基金National Natural Science Foundation of China(11705100)Youth Innovations and Talents Project of Shandong Provincial Colleges,and Universities(201909118)Higher Educational Youth Innovation Science and Technology Program Shandong Province(2020KJJ004)National Natural Science Foundation of China(11975151,11675101,11961141003)MOE Key Lab for Particle Physics,Astrophysics and Cosmology for financial support。
文摘In this paper,we propose an approach to nucleon-pair approximation(NPA)with m-scheme bases,in which the collective nucleon pairs are represented in terms of antisymmetric matrices,and commutations between nucleon pairs are given using a matrix multiplication that avoids angular-momentum couplings and recouplings.Therefore the present approach significantly simplifies the NPA computation.Furthermore,it is formulated on the same footing with and without isospin.
基金supported by the Swiss National Science Foundation and the European Commission(COAST project EUFP6-IST-FET Contract 033664).
文摘In order to model the dispersal of volcanic particles in the atmosphere and their deposition on the ground,one has to simulate an advection-diffusionsedimentation process on a large spatial area.Here we compare a Lattice Boltzmann and a Cellular Automata approach.Our results show that for high Peclet regimes,the cellular automata model produce results that are as accurate as the lattice Boltzmann model and is computationally more effective.
