In this study, combustion of methane was simulated using four kinetic models of methane in CHEMKIN 4.1.1 for 0-D closed internal combustion （IC） engine reactor. Two detailed （GRIMECH3.0 ＆ UBC MECH2.0） and two red...In this study, combustion of methane was simulated using four kinetic models of methane in CHEMKIN 4.1.1 for 0-D closed internal combustion （IC） engine reactor. Two detailed （GRIMECH3.0 ＆ UBC MECH2.0） and two reduced （One step ＆ Four steps） models were examined for various IC engine designs. The detailed models （GRIMECH3.0, ＆ UBC MECH2.0） and 4-step models successfully predicted the combustion while global model was unable to predict any combustion reaction. This study illustrated that the detailed model showed good concordances in the prediction of chamber pressure, temperature and major combustion species profiles. The detailed models also exhibited the capabilities to predict the pollutants formation in an IC engine while the reduced schemes showed failure in the prediction of pollutants emissions. Although, there are discrepancies among the profiles of four considered model, the detailed models （GRIMECH3.0 ＆ UBC MECH2.0） produced the acceptable agreement in the species prediction and formation of pollutants.展开更多
This paper discusses a physics-informed methodology aimed at reconstructing efficiently the fluid state of a system.Herein,the generation of an accurate reduced order model of twodimensional unsteady flows from data l...This paper discusses a physics-informed methodology aimed at reconstructing efficiently the fluid state of a system.Herein,the generation of an accurate reduced order model of twodimensional unsteady flows from data leverages on sparsity-promoting statistical learning techniques.The cornerstone of the approach is l_(1) regularised regression,resulting in sparselyconnected models where only the important quadratic interactions between modes are retained.The original dynamical behaviour is reproduced at low computational costs,as few quadratic interactions need to be evaluated.The approach has two key features.First,interactions are selected systematically as a solution of a convex optimisation problem and no a priori assumptions on the physics of the flow are required.Second,the presence of a regularisation term improves the predictive performance of the original model,generally affected by noise and poor data quality.Test cases are for two-dimensional lid-driven cavity flows,at three values of the Reynolds number for which the motion is chaotic and energy interactions are scattered across the spectrum.It is found that:(A)the sparsification generates models maintaining the original accuracy level but with a lower number of active coefficients;this becomes more pronounced for increasing Reynolds numbers suggesting that extension of these techniques to real-life flow configurations is possible;(B)sparse models maintain a good temporal stability for predictions.The methodology is ready for more complex applications without modifications of the underlying theory,and the integration into a cyberphysical model is feasible.展开更多
To enhance the prediction accuracy of unsteady wakes behind wind turbines,a novel reduced-order model is proposed by integrating a multifunctional recurrent fuzzy neural network(MFRFNN)and proper orthogonal decom-posi...To enhance the prediction accuracy of unsteady wakes behind wind turbines,a novel reduced-order model is proposed by integrating a multifunctional recurrent fuzzy neural network(MFRFNN)and proper orthogonal decom-position(POD).First,POD is employed to reduce the di-mensionality of the wind field data,extracting spatiotempo-rally correlated modal coefficients and modes.These reduced-order variables can effectively capture the essential features of unsteady wake behaviors.Next,MFRFNN is utilized to predict the time series of modal coefficients.Fi-nally,by combining the predicted modal coefficients with their corresponding modes,a flow field is reconstructed,al-lowing accurate prediction of unsteady wake dynamics.The predicted wake data exhibit high consistency with large eddy simulation results in both the near-and far-wake re-gions and outperform existing data-driven methods.This ap-proach offers significant potential for optimizing wind farm design and provides a new solution for the precise prediction of wind turbine wake behavior.展开更多
During the EAST radiative divertor experiments,one of the key challenges was how to avoid the occurrence of disruptive events caused by excessive impurity seeding.To estimate the required impurity fraction for diverto...During the EAST radiative divertor experiments,one of the key challenges was how to avoid the occurrence of disruptive events caused by excessive impurity seeding.To estimate the required impurity fraction for divertor detachment,we introduce a reduced edge plasma radiation model.In the model,based on the momentum conservation along the magnetic field line,the upstream pressure is determined by the plasma density and temperature at the divertor target,and then the impurity radiation loss is obtained by the balance of the heat and particle fluxes.It is found that the required impurity fraction shows a non-monotonic variation with divertor electron temperature(T_(d))when 0.1 eV<T_(d)<10 eV.In the range of 0.1 eV<T_(d)<1 e V,the position near the valley of required impurity fraction corresponds to strong plasma recombination.Due to the dependence of the volumetric momentum loss effect on the T_(d)in the range of 1 eV<T_(d)<10 eV,the required impurity fraction peaks and then decreases as T_(d)is increased.Compared to neon,the usage of argon reduces the impurity fraction by about twice.In addition,for the various fitting parameters in the pressure-momentum loss model,it is shown that the tendency of required impurity fraction with T_(d)always increases first and then decreases in the range of 1 eV<T_(d)<10 eV,but the required impurity fraction decreases when the model that characterizes the strong loss in pressure momentum is used.展开更多
Aerothermoelasticity is one of the key technologies for hypersonic vehicles. Accurate and efficient computation of the aerothermodynamics is one of the primary challenges for hypersonic aerothermoelastic analysis. Aim...Aerothermoelasticity is one of the key technologies for hypersonic vehicles. Accurate and efficient computation of the aerothermodynamics is one of the primary challenges for hypersonic aerothermoelastic analysis. Aimed at solving the shortcomings of engineering calculation, compu- tation fluid dynamics （CFD） and experimental investigation, a reduced order modeling （ROM） framework for aerothermodynamics based on CFD predictions using an enhanced algorithm of fast maximin Latin hypercube design is developed. Both proper orthogonal decomposition （POD） and surrogate are considered and compared to construct ROMs. Two surrogate approaches named Kriging and optimized radial basis function （ORBF） are utilized to construct ROMs. Furthermore, an enhanced algorithm of fast maximin Latin hypercube design is proposed, which proves to be helpful to improve the precisions of ROMs. Test results for the three-dimensional aerothermody- namic over a hypersonic surface indicate that： the ROMs precision based on Kriging is better than that by ORBF, ROMs based on Kriging are marginally more accurate than ROMs based on POD- Kriging. In a word, the ROM framework for hypersonic aerothermodynamics has good precision and efficiency.展开更多
This paper describes a method proposed for modeling large deflection of aircraft in nonlinear aeroelastic analysis by developing reduced order model（ROM）.The method is applied for solving the static aeroelastic and ...This paper describes a method proposed for modeling large deflection of aircraft in nonlinear aeroelastic analysis by developing reduced order model（ROM）.The method is applied for solving the static aeroelastic and static aeroelastic trim problems of flexible aircraft containing geometric nonlinearities;meanwhile,the non-planar effects of aerodynamics and follower force effect have been considered.ROMs are computational inexpensive mathematical representations compared to traditional nonlinear finite element method（FEM） especially in aeroelastic solutions.The approach for structure modeling presented here is on the basis of combined modal/finite element（MFE） method that characterizes the stiffness nonlinearities and we apply that structure modeling method as ROM to aeroelastic analysis.Moreover,the non-planar aerodynamic force is computed by the non-planar vortex lattice method（VLM）.Structure and aerodynamics can be coupled with the surface spline method.The results show that both of the static aeroelastic analysis and trim analysis of aircraft based on structure ROM can achieve a good agreement compared to analysis based on the FEM and experimental result.展开更多
Reduced order models(ROMs) based on the snapshots on the CFD high-fidelity simulations have been paid great attention recently due to their capability of capturing the features of the complex geometries and flow confi...Reduced order models(ROMs) based on the snapshots on the CFD high-fidelity simulations have been paid great attention recently due to their capability of capturing the features of the complex geometries and flow configurations. To improve the efficiency and precision of the ROMs, it is indispensable to add extra sampling points to the initial snapshots, since the number of sampling points to achieve an adequately accurate ROM is generally unknown in prior, but a large number of initial sampling points reduces the parsimony of the ROMs. A fuzzy-clustering-based adding-point strategy is proposed and the fuzzy clustering acts an indicator of the region in which the precision of ROMs is relatively low. The proposed method is applied to construct the ROMs for the benchmark mathematical examples and a numerical example of hypersonic aerothermodynamics prediction for a typical control surface. The proposed method can achieve a 34.5% improvement on the efficiency than the estimated mean squared error prediction algorithm and shows same-level prediction accuracy.展开更多
The improved line sampling （LS） technique, an effective numerical simulation method, is employed to analyze the probabilistic characteristics and reliability sensitivity of flutter with random structural parameter i...The improved line sampling （LS） technique, an effective numerical simulation method, is employed to analyze the probabilistic characteristics and reliability sensitivity of flutter with random structural parameter in transonic flow. The improved LS technique is a novel methodology for reliability and sensitivity analysis of high dimensionality and low probability problem with implicit limit state function, and it does not require any approximating surrogate of the implicit limit state equation. The improved LS is used to estimate the flutter reliability and the sensitivity of a two-dimensional wing, in which some structural properties, such as frequency, parameters of gravity center and mass ratio, are considered as random variables. Computational fluid dynamics （CFD） based unsteady aerodynamic reduced order model （ROM） method is used to construct the aerodynamic state equations. Coupling structural state equations with aerodynamic state equations, the safety margin of flutter is founded by using the critical velocity of flutter. The results show that the improved LS technique can effectively decrease the computational cost in the random uncertainty analysis of flutter. The reliability sensitivity, defined by the partial derivative of the failure probability with respect to the distribution parameter of random variable, can help to identify the important parameters and guide the structural optimization design.展开更多
Based on Recursive Radial Basis Function(RRBF)neural network,the Reduced Order Model(ROM)of compressor cascade was established to meet the urgent demand of highly efficient prediction of unsteady aerodynamics performa...Based on Recursive Radial Basis Function(RRBF)neural network,the Reduced Order Model(ROM)of compressor cascade was established to meet the urgent demand of highly efficient prediction of unsteady aerodynamics performance of turbomachinery.One novel ROM called ASA-RRBF model based on Adaptive Simulated Annealing(ASA)algorithm was developed to enhance the generalization ability of the unsteady ROM.The ROM was verified by predicting the unsteady aerodynamics performance of a highly-loaded compressor cascade.The results show that the RRBF model has higher accuracy in identification of the dimensionless total pressure and dimensionless static pressure of compressor cascade under nonlinear and unsteady conditions,and the model behaves higher stability and computational efficiency.However,for the strong nonlinear characteristics of aerodynamic parameters,the RRBF model presents lower accuracy.Additionally,the RRBF model predicts with a large error in the identification of aerodynamic parameters under linear and unsteady conditions.For ASA-RRBF,by introducing a small-amplitude and highfrequency sinusoidal signal as validation sample,the width of the basis function of the RRBF model is optimized to improve the generalization ability of the ROM under linear unsteady conditions.Besides,this model improves the predicting accuracy of dimensionless static pressure which has strong nonlinear characteristics.The ASA-RRBF model has higher prediction accuracy than RRBF model without significantly increasing the total time consumption.This novel model can predict the linear hysteresis of dimensionless static pressure happened in the harmonic condition,but it cannot accurately predict the beat frequency of dimensionless total pressure.展开更多
The hydraulic fracturing is a nonlinear,fluid-solid coupling and transient problem,in most cases it is always time-consuming to simulate this process numerically.In recent years,although many numerical methods were pr...The hydraulic fracturing is a nonlinear,fluid-solid coupling and transient problem,in most cases it is always time-consuming to simulate this process numerically.In recent years,although many numerical methods were proposed to settle this problem,most of them still require a large amount of computer resources.Thus it is a high demand to develop more efficient numerical approaches to achieve the real-time monitoring of the fracture geometry during the hydraulic fracturing treatment.In this study,a reduced order modeling technique namely Proper Generalized Decomposition(PGD),is applied to accelerate the simulations of the transient,non-linear coupled system of hydraulic fracturing problem,to match this extremely tight response time constraint.The separability of the solution in space and time dimensions is studied for a simplified model problem.The solid and fluid equations are coupled explicitly by inverting the solid discrete problem,and a simple iterative procedure to handle the non-linear characteristic of the hydraulic fracturing problem is proposed in this work.Numeral validation illustrates that the results of PGD match well with these of standard finite element method in terms o f fracture opening and fluid pressure in the hydro-fracture.Moreover,after the off-line calculations,the numerical results can be obtained in real time.展开更多
As a promising numerical tool of structural dynamics in mid- and high frequencies, the wave and finite element method（WFEM） is receiving increasingly attention and applications. In this paper, an enhanced WFEM has b...As a promising numerical tool of structural dynamics in mid- and high frequencies, the wave and finite element method（WFEM） is receiving increasingly attention and applications. In this paper, an enhanced WFEM has been developed with a reduced model and a new eigenvalue scheme. The reduced model is applicable for structures with piezoelectric shunts or local dampers;the new eigenvalue scheme can mitigate the ill-conditioning when the wave basis is calculated. The enhanced WFEM is applied to a thin-wall structure with periodically distributed piezoelectric materials（PZT）. Both free wave characteristics and forced response are analyzed and the influences of the suggested enhancements are presented. It is shown that if the control factors are properly chosen, these enhancements can improve the accuracy while accelerating the calculation. Resulting from the complexity of the application, these enhancements are not optional but imperative.展开更多
In this paper, we study the price of catastrophe Options with counterparty credit risk in a reduced form model. We assume that the loss process is generated by a doubly stochastic Poisson process, the share price proc...In this paper, we study the price of catastrophe Options with counterparty credit risk in a reduced form model. We assume that the loss process is generated by a doubly stochastic Poisson process, the share price process is modeled through a jump-diffusion process which is correlated to the loss process, the interest rate process and the default intensity process are modeled through the Vasicek model： We derive the closed form formulae for pricing catastrophe options in a reduced form model. Furthermore, we make some numerical analysis on the explicit formulae.展开更多
Active stability augmentation system is an attractive and promising technology to suppress flutter and limit cycle oscillation (LCO). In order to design a good active control law, the control plant model with low orde...Active stability augmentation system is an attractive and promising technology to suppress flutter and limit cycle oscillation (LCO). In order to design a good active control law, the control plant model with low order and high accuracy must be provided, which is one of the most important key points. The traditional model is based on low fidelity aerodynamics model such as panel method, which is unsuitable for transonic flight regime. The physics-based high fidelity tools, reduced order model (ROM) and CFD/CSD coupled aeroservoelastic solver are used to design the active control law. The Volterra/ROM is applied to constructing the low order state space model for the nonlinear unsteady aerodynamics and static output feedback method is used to active control law design. The detail of the new method is demonstrated by the Goland+ wing/store system. The simulation results show that the effectiveness of the designed active augmentation system, which can suppress the flutter and LCO successfully.展开更多
The modeling of dynamic stall aerodynamics is essential to stall flutter, due to the flow separation in a large-amplitude pitching oscillation process. A newly neural network based Reduced Order Model(ROM) framework f...The modeling of dynamic stall aerodynamics is essential to stall flutter, due to the flow separation in a large-amplitude pitching oscillation process. A newly neural network based Reduced Order Model(ROM) framework for predicting the aerodynamic forces of an airfoil undergoing large-amplitude pitching oscillation at various velocities is presented in this work. First, the dynamic stall aerodynamics is calculated by solving RANS equations and the transitional SST-γ model. Afterwards, the stall flutter bifurcation behavior is calculated by the above CFD solver coupled with structural dynamic equation. The critical flutter speed and limit-cycle oscillation amplitudes are consistent with those obtained by experiments. A newly multi-layer Gated Recurrent Unit(GRU) neural network based ROM is constructed to accelerate the calculation of aerodynamic forces. The training and validation process are carried out upon the unsteady aerodynamic data obtained by the proposed CFD method. The well-trained ROM is then coupled with the structure equation at a specific velocity, the Limit-Cycle Oscillation(LCO) of stall flutter under this flow condition is predicted precisely and more quickly. In order to predict both the critical flutter velocity and LCO amplitudes after bifurcation at different velocities, a new ROM with GRU neural network considering the variation of flow velocities is developed. The stall flutter results predicted by ROM agree well with the CFD ones at different velocities. Finally, a brief sensitivity analysis of two structural parameters of ROM is carried out. It infers the potential of the presented modeling method to depict the nonlinearity of dynamic stall and stall flutter phenomenon.展开更多
Designing effective control policy requires accurate quantification of the relationship between the ambient concentrations of O3and PM2.5and the emissions of their precursors.However,the challenge is that precursor re...Designing effective control policy requires accurate quantification of the relationship between the ambient concentrations of O3and PM2.5and the emissions of their precursors.However,the challenge is that precursor reduction does not necessarily lead to decreases in the concentrations of O3and PM2.5,which are formed by multiple precursors under complex physical and chemical processes;this calls for the development of advanced model technologies to provide accurate predictions of the nonlinear responses of air quality to emissions.Different from the traditional sensitivity analysis and source apportionment methods,the reduced form models(RFMs)based on chemical transport models(CTMs)are able to quantify air quality responses to emissions more accurately and efficiently with lower computational cost.Here we review recent approaches used in RFMs and compare their structures,advantages and disadvantages,performance and applications.In general,RFMs are classified into three types including(1)sensitivity-based models,(2)models with simplified chemistry and physical processes,and(3)statistical models,with considerable differences in principles,characteristics and application ranges.The prediction of nonlinear responses by RFMs enables more in-depth analysis,not only in terms of real-time prediction of concentrations and quantification of human exposure,health impacts and economic damage,but also in optimizing control policies.Notably,data assimilation and emission inventory inversion based on the nonlinear response of concentrations to emissions can also be greatly beneficial to air pollution control management.In future studies,improvement in the performance of CTMs is exceedingly crucial to obtain a more reliable baseline for the prediction of air quality responses.Development of models to determine the air quality response to emissions under varying meteorological conditions is also necessary in the context of future climate changes,which pose great challenges to the quantification of response relationships.Additionally,with rising requirements for fine-scale air quality management,improving the performance of urban-scale simulations is worth considering.In short,accurate predictions of the response of air quality to emissions,though challenging,holds great promise for the present as well as for future scenarios.展开更多
The optimisation of earthquake resistance of high buildings by multi-tuned mass dampers was investigated using bionic algorithms. In bionic or evolutionary optimisation studies the properties of parents are crossed an...The optimisation of earthquake resistance of high buildings by multi-tuned mass dampers was investigated using bionic algorithms. In bionic or evolutionary optimisation studies the properties of parents are crossed and mutated to produce a new generation with slightly different properties. The kids which best satisfy the object of the study, become the parents of the next generation. After a series of generations essential improvements of the object may be observed. Tuned mass dampers are widely used to reduce the impact of dynamic excitations on structures. A single mass system and multi-mass oscillators help to explain the mechanics of the dampers. To apply the bionic optimisation strategy to high buildings with passive tuned mass dampers subject to seismic loading a special beam element has been developed. In addition to the 6 degrees of freedom of a conventional beam element, it has 2 degrees of freedom for the displacements of the dampers. It allows for fast studies of many variants. As central result, efficient designs for damping systems along the height of an edifice are found. The impact on the structure may be reduced essentially by the use of such dampers designed to interact in an optimal way.展开更多
Fastening failures have frequently been found on China high-speed railway curved tracks in recent years.Thus the influence of fastening failures on high-speed train-track interaction in curved track needs to be analyz...Fastening failures have frequently been found on China high-speed railway curved tracks in recent years.Thus the influence of fastening failures on high-speed train-track interaction in curved track needs to be analyzed.A train-curved slab track interaction model is built,in which the real shape of the curved rail is considered and modeled with reduced beam model(RBM)and curved beam theory,and the slabs are modeled with four-nodes Kirchhoff-Love plate elements.The present model is validated at first with different traditional models.Then the influence of fastening failure in curved slab track on train-track interaction dynamics is studied.A different number of failed fastenings is assumed to occur at the curved track,and different types of fastening failure including the fatigue fracture of the clip structure and failure of the rail pad are considered.Based on the calculation results,the fatigue fracture of the clip structure has little influence on train-track interaction dynamics.But when rail pad failure happens and its equivalent vertical stiffness and damping are less than one-tenth of its original,the fastening failure seriously affects the high-speed train operation safety,and it must be prevented.展开更多
Accurate and efficient online parameter identification and state estimation are crucial for leveraging digital twin simulations to optimize the operation of near-carbon-free nuclear energy systems.In previous studies,...Accurate and efficient online parameter identification and state estimation are crucial for leveraging digital twin simulations to optimize the operation of near-carbon-free nuclear energy systems.In previous studies,we developed a reactor operation digital twin(RODT).However,non-differentiabilities and discontinuities arise when employing machine learning-based surrogate forward models,challenging traditional gradient-based inverse methods and their variants.This study investigated deterministic and metaheuristic algorithms and developed hybrid algorithms to address these issues.An efficient modular RODT software framework that incorporates these methods into its post-evaluation module is presented for comprehensive comparison.The methods were rigorously assessed based on convergence profiles,stability with respect to noise,and computational performance.The numerical results show that the hybrid KNNLHS algorithm excels in real-time online applications,balancing accuracy and efficiency with a prediction error rate of only 1%and processing times of less than 0.1 s.Contrastingly,algorithms such as FSA,DE,and ADE,although slightly slower(approximately 1 s),demonstrated higher accuracy with a 0.3%relative L_2 error,which advances RODT methodologies to harness machine learning and system modeling for improved reactor monitoring,systematic diagnosis of off-normal events,and lifetime management strategies.The developed modular software and novel optimization methods presented offer pathways to realize the full potential of RODT for transforming energy engineering practices.展开更多
A computationally efficient two-surface plasticity model is assessed against crystal plasticity. Focus is laid on the mechanical behavior of magnesium alloys in the presence of ductility-limiting defects, such as void...A computationally efficient two-surface plasticity model is assessed against crystal plasticity. Focus is laid on the mechanical behavior of magnesium alloys in the presence of ductility-limiting defects, such as voids. The two surfaces separately account for slip and twinning such that the constitutive formulation captures the evolving plastic anisotropy and evolving tension-compression asymmetry. For model identification, a procedure is proposed whereby the initial guess is based on a combination of experimental data and computationally intensive polycrystal calculations from the literature. In drawing direct comparisons with crystal plasticity, of which the proposed model constitutes a heuristically derived reduced-order model, the available crystal plasticity simulations are grouped in two datasets. A calibration set contains minimal data for both pristine and porous material subjected to one loading path. Then the two-surface model is assessed against a broader set of crystal plasticity simulations for voided unit cells under various stress states and two loading orientations. The assessment also includes microstructure evolution(rate of growth of porosity and void distortion). The ability of the two-surface model to capture essential features of crystal plasticity is analyzed along with an evaluation of computational cost. The prospects of using the model in guiding the development of physically sound damage models in Mg alloys are put forth in the context of high-throughput simulations.展开更多
A Reduced Order Model(ROM)based analysis method for turbomachinery cascade coupled mode flutter is presented in this paper.The unsteady aerodynamic model is established by a system identification technique combined wi...A Reduced Order Model(ROM)based analysis method for turbomachinery cascade coupled mode flutter is presented in this paper.The unsteady aerodynamic model is established by a system identification technique combined with a set of Aerodynamic Influence Coefficients(AIC).Subsequently,the aerodynamic model is encoded into the state space and then coupled with the structural dynamic equations,resulting in a ROM of the cascade aeroelasticity.The cascade flutter can be determined by solving the eigenvalues of the ROM.Bending-torsional coupled mode flutter analysis for the Standard Configuration Eleven(SC11)cascade is used to validate the proposed method.展开更多
文摘In this study, combustion of methane was simulated using four kinetic models of methane in CHEMKIN 4.1.1 for 0-D closed internal combustion （IC） engine reactor. Two detailed （GRIMECH3.0 ＆ UBC MECH2.0） and two reduced （One step ＆ Four steps） models were examined for various IC engine designs. The detailed models （GRIMECH3.0, ＆ UBC MECH2.0） and 4-step models successfully predicted the combustion while global model was unable to predict any combustion reaction. This study illustrated that the detailed model showed good concordances in the prediction of chamber pressure, temperature and major combustion species profiles. The detailed models also exhibited the capabilities to predict the pollutants formation in an IC engine while the reduced schemes showed failure in the prediction of pollutants emissions. Although, there are discrepancies among the profiles of four considered model, the detailed models （GRIMECH3.0 ＆ UBC MECH2.0） produced the acceptable agreement in the species prediction and formation of pollutants.
文摘This paper discusses a physics-informed methodology aimed at reconstructing efficiently the fluid state of a system.Herein,the generation of an accurate reduced order model of twodimensional unsteady flows from data leverages on sparsity-promoting statistical learning techniques.The cornerstone of the approach is l_(1) regularised regression,resulting in sparselyconnected models where only the important quadratic interactions between modes are retained.The original dynamical behaviour is reproduced at low computational costs,as few quadratic interactions need to be evaluated.The approach has two key features.First,interactions are selected systematically as a solution of a convex optimisation problem and no a priori assumptions on the physics of the flow are required.Second,the presence of a regularisation term improves the predictive performance of the original model,generally affected by noise and poor data quality.Test cases are for two-dimensional lid-driven cavity flows,at three values of the Reynolds number for which the motion is chaotic and energy interactions are scattered across the spectrum.It is found that:(A)the sparsification generates models maintaining the original accuracy level but with a lower number of active coefficients;this becomes more pronounced for increasing Reynolds numbers suggesting that extension of these techniques to real-life flow configurations is possible;(B)sparse models maintain a good temporal stability for predictions.The methodology is ready for more complex applications without modifications of the underlying theory,and the integration into a cyberphysical model is feasible.
基金The National Natural Science Foundation of China (No. 51908107)。
文摘To enhance the prediction accuracy of unsteady wakes behind wind turbines,a novel reduced-order model is proposed by integrating a multifunctional recurrent fuzzy neural network(MFRFNN)and proper orthogonal decom-position(POD).First,POD is employed to reduce the di-mensionality of the wind field data,extracting spatiotempo-rally correlated modal coefficients and modes.These reduced-order variables can effectively capture the essential features of unsteady wake behaviors.Next,MFRFNN is utilized to predict the time series of modal coefficients.Fi-nally,by combining the predicted modal coefficients with their corresponding modes,a flow field is reconstructed,al-lowing accurate prediction of unsteady wake dynamics.The predicted wake data exhibit high consistency with large eddy simulation results in both the near-and far-wake re-gions and outperform existing data-driven methods.This ap-proach offers significant potential for optimizing wind farm design and provides a new solution for the precise prediction of wind turbine wake behavior.
基金supported by National Natural Science Foundation of China(No.12375227)Innovation in Fusion Engineering Technology of Institute(No.E35QT1080C)。
文摘During the EAST radiative divertor experiments,one of the key challenges was how to avoid the occurrence of disruptive events caused by excessive impurity seeding.To estimate the required impurity fraction for divertor detachment,we introduce a reduced edge plasma radiation model.In the model,based on the momentum conservation along the magnetic field line,the upstream pressure is determined by the plasma density and temperature at the divertor target,and then the impurity radiation loss is obtained by the balance of the heat and particle fluxes.It is found that the required impurity fraction shows a non-monotonic variation with divertor electron temperature(T_(d))when 0.1 eV<T_(d)<10 eV.In the range of 0.1 eV<T_(d)<1 e V,the position near the valley of required impurity fraction corresponds to strong plasma recombination.Due to the dependence of the volumetric momentum loss effect on the T_(d)in the range of 1 eV<T_(d)<10 eV,the required impurity fraction peaks and then decreases as T_(d)is increased.Compared to neon,the usage of argon reduces the impurity fraction by about twice.In addition,for the various fitting parameters in the pressure-momentum loss model,it is shown that the tendency of required impurity fraction with T_(d)always increases first and then decreases in the range of 1 eV<T_(d)<10 eV,but the required impurity fraction decreases when the model that characterizes the strong loss in pressure momentum is used.
基金supported by the National Natural Science Foundation of China (Nos. 11372036, 50875024)Excellent Young Scholars Research Fund of Beijing Institute of Technology of China (No. 2010Y0102)
文摘Aerothermoelasticity is one of the key technologies for hypersonic vehicles. Accurate and efficient computation of the aerothermodynamics is one of the primary challenges for hypersonic aerothermoelastic analysis. Aimed at solving the shortcomings of engineering calculation, compu- tation fluid dynamics （CFD） and experimental investigation, a reduced order modeling （ROM） framework for aerothermodynamics based on CFD predictions using an enhanced algorithm of fast maximin Latin hypercube design is developed. Both proper orthogonal decomposition （POD） and surrogate are considered and compared to construct ROMs. Two surrogate approaches named Kriging and optimized radial basis function （ORBF） are utilized to construct ROMs. Furthermore, an enhanced algorithm of fast maximin Latin hypercube design is proposed, which proves to be helpful to improve the precisions of ROMs. Test results for the three-dimensional aerothermody- namic over a hypersonic surface indicate that： the ROMs precision based on Kriging is better than that by ORBF, ROMs based on Kriging are marginally more accurate than ROMs based on POD- Kriging. In a word, the ROM framework for hypersonic aerothermodynamics has good precision and efficiency.
文摘This paper describes a method proposed for modeling large deflection of aircraft in nonlinear aeroelastic analysis by developing reduced order model（ROM）.The method is applied for solving the static aeroelastic and static aeroelastic trim problems of flexible aircraft containing geometric nonlinearities;meanwhile,the non-planar effects of aerodynamics and follower force effect have been considered.ROMs are computational inexpensive mathematical representations compared to traditional nonlinear finite element method（FEM） especially in aeroelastic solutions.The approach for structure modeling presented here is on the basis of combined modal/finite element（MFE） method that characterizes the stiffness nonlinearities and we apply that structure modeling method as ROM to aeroelastic analysis.Moreover,the non-planar aerodynamic force is computed by the non-planar vortex lattice method（VLM）.Structure and aerodynamics can be coupled with the surface spline method.The results show that both of the static aeroelastic analysis and trim analysis of aircraft based on structure ROM can achieve a good agreement compared to analysis based on the FEM and experimental result.
基金Supported by National Natural Science Foundation of China(Grant No.11372036)
文摘Reduced order models(ROMs) based on the snapshots on the CFD high-fidelity simulations have been paid great attention recently due to their capability of capturing the features of the complex geometries and flow configurations. To improve the efficiency and precision of the ROMs, it is indispensable to add extra sampling points to the initial snapshots, since the number of sampling points to achieve an adequately accurate ROM is generally unknown in prior, but a large number of initial sampling points reduces the parsimony of the ROMs. A fuzzy-clustering-based adding-point strategy is proposed and the fuzzy clustering acts an indicator of the region in which the precision of ROMs is relatively low. The proposed method is applied to construct the ROMs for the benchmark mathematical examples and a numerical example of hypersonic aerothermodynamics prediction for a typical control surface. The proposed method can achieve a 34.5% improvement on the efficiency than the estimated mean squared error prediction algorithm and shows same-level prediction accuracy.
基金Foundation items： National Natural Science Foundation of China （NSFC 10572117, 10802063, 50875213） National High-tech Research and Development Program （2007AA04Z401）+2 种基金 Aeronautical Science Foundation of China （2007ZA53012） New Century Program For Excellent Talents of Ministry of Education of China （NCET-05-0868） Ph.D. Program Foundation of Northwestern Polytechnical University （CX200801）.
文摘The improved line sampling （LS） technique, an effective numerical simulation method, is employed to analyze the probabilistic characteristics and reliability sensitivity of flutter with random structural parameter in transonic flow. The improved LS technique is a novel methodology for reliability and sensitivity analysis of high dimensionality and low probability problem with implicit limit state function, and it does not require any approximating surrogate of the implicit limit state equation. The improved LS is used to estimate the flutter reliability and the sensitivity of a two-dimensional wing, in which some structural properties, such as frequency, parameters of gravity center and mass ratio, are considered as random variables. Computational fluid dynamics （CFD） based unsteady aerodynamic reduced order model （ROM） method is used to construct the aerodynamic state equations. Coupling structural state equations with aerodynamic state equations, the safety margin of flutter is founded by using the critical velocity of flutter. The results show that the improved LS technique can effectively decrease the computational cost in the random uncertainty analysis of flutter. The reliability sensitivity, defined by the partial derivative of the failure probability with respect to the distribution parameter of random variable, can help to identify the important parameters and guide the structural optimization design.
基金co-National Science and Technology Major Project(No.2017-II-0009-0023)Innovation Guidance Support Project for Taicang Top Research Institutes(No.TC2019DYDS09)。
文摘Based on Recursive Radial Basis Function(RRBF)neural network,the Reduced Order Model(ROM)of compressor cascade was established to meet the urgent demand of highly efficient prediction of unsteady aerodynamics performance of turbomachinery.One novel ROM called ASA-RRBF model based on Adaptive Simulated Annealing(ASA)algorithm was developed to enhance the generalization ability of the unsteady ROM.The ROM was verified by predicting the unsteady aerodynamics performance of a highly-loaded compressor cascade.The results show that the RRBF model has higher accuracy in identification of the dimensionless total pressure and dimensionless static pressure of compressor cascade under nonlinear and unsteady conditions,and the model behaves higher stability and computational efficiency.However,for the strong nonlinear characteristics of aerodynamic parameters,the RRBF model presents lower accuracy.Additionally,the RRBF model predicts with a large error in the identification of aerodynamic parameters under linear and unsteady conditions.For ASA-RRBF,by introducing a small-amplitude and highfrequency sinusoidal signal as validation sample,the width of the basis function of the RRBF model is optimized to improve the generalization ability of the ROM under linear unsteady conditions.Besides,this model improves the predicting accuracy of dimensionless static pressure which has strong nonlinear characteristics.The ASA-RRBF model has higher prediction accuracy than RRBF model without significantly increasing the total time consumption.This novel model can predict the linear hysteresis of dimensionless static pressure happened in the harmonic condition,but it cannot accurately predict the beat frequency of dimensionless total pressure.
基金the National Science Foundation of China(Grant Nos.51804033 and 51936001)China Postdoctoral Science and Foundation(Grant No.2018M641254)+3 种基金Beijing Postdoctoral Research Foundation(2018-ZZ-045)the Project of Construction of Innovative Teams and Teacher Career Development for Universities and Colleges Under Beijing Municipality(Grant No.IDHT20170507)Program of Great Wall Scholar(Grant No.CIT&TCD20180313)Jointly Projects of Beijing Natural Science Foundation and Beijing Municipal Education Commission(Grant No.KZ201810017023).
文摘The hydraulic fracturing is a nonlinear,fluid-solid coupling and transient problem,in most cases it is always time-consuming to simulate this process numerically.In recent years,although many numerical methods were proposed to settle this problem,most of them still require a large amount of computer resources.Thus it is a high demand to develop more efficient numerical approaches to achieve the real-time monitoring of the fracture geometry during the hydraulic fracturing treatment.In this study,a reduced order modeling technique namely Proper Generalized Decomposition(PGD),is applied to accelerate the simulations of the transient,non-linear coupled system of hydraulic fracturing problem,to match this extremely tight response time constraint.The separability of the solution in space and time dimensions is studied for a simplified model problem.The solid and fluid equations are coupled explicitly by inverting the solid discrete problem,and a simple iterative procedure to handle the non-linear characteristic of the hydraulic fracturing problem is proposed in this work.Numeral validation illustrates that the results of PGD match well with these of standard finite element method in terms o f fracture opening and fluid pressure in the hydro-fracture.Moreover,after the off-line calculations,the numerical results can be obtained in real time.
基金the company PSA Peugeot Citroёn for the financial support
文摘As a promising numerical tool of structural dynamics in mid- and high frequencies, the wave and finite element method（WFEM） is receiving increasingly attention and applications. In this paper, an enhanced WFEM has been developed with a reduced model and a new eigenvalue scheme. The reduced model is applicable for structures with piezoelectric shunts or local dampers;the new eigenvalue scheme can mitigate the ill-conditioning when the wave basis is calculated. The enhanced WFEM is applied to a thin-wall structure with periodically distributed piezoelectric materials（PZT）. Both free wave characteristics and forced response are analyzed and the influences of the suggested enhancements are presented. It is shown that if the control factors are properly chosen, these enhancements can improve the accuracy while accelerating the calculation. Resulting from the complexity of the application, these enhancements are not optional but imperative.
基金supported by the National Natural Science Foundation of China(11371274)
文摘In this paper, we study the price of catastrophe Options with counterparty credit risk in a reduced form model. We assume that the loss process is generated by a doubly stochastic Poisson process, the share price process is modeled through a jump-diffusion process which is correlated to the loss process, the interest rate process and the default intensity process are modeled through the Vasicek model： We derive the closed form formulae for pricing catastrophe options in a reduced form model. Furthermore, we make some numerical analysis on the explicit formulae.
基金National Natural Science Foundation of China (10902082)New Faculty Research Foundation of XJTUthe Fundamental Research Funds for the Central Universities (xjj20100126)
文摘Active stability augmentation system is an attractive and promising technology to suppress flutter and limit cycle oscillation (LCO). In order to design a good active control law, the control plant model with low order and high accuracy must be provided, which is one of the most important key points. The traditional model is based on low fidelity aerodynamics model such as panel method, which is unsuitable for transonic flight regime. The physics-based high fidelity tools, reduced order model (ROM) and CFD/CSD coupled aeroservoelastic solver are used to design the active control law. The Volterra/ROM is applied to constructing the low order state space model for the nonlinear unsteady aerodynamics and static output feedback method is used to active control law design. The detail of the new method is demonstrated by the Goland+ wing/store system. The simulation results show that the effectiveness of the designed active augmentation system, which can suppress the flutter and LCO successfully.
基金supported by the National Natural Science Foundation of China(No.11672018).
文摘The modeling of dynamic stall aerodynamics is essential to stall flutter, due to the flow separation in a large-amplitude pitching oscillation process. A newly neural network based Reduced Order Model(ROM) framework for predicting the aerodynamic forces of an airfoil undergoing large-amplitude pitching oscillation at various velocities is presented in this work. First, the dynamic stall aerodynamics is calculated by solving RANS equations and the transitional SST-γ model. Afterwards, the stall flutter bifurcation behavior is calculated by the above CFD solver coupled with structural dynamic equation. The critical flutter speed and limit-cycle oscillation amplitudes are consistent with those obtained by experiments. A newly multi-layer Gated Recurrent Unit(GRU) neural network based ROM is constructed to accelerate the calculation of aerodynamic forces. The training and validation process are carried out upon the unsteady aerodynamic data obtained by the proposed CFD method. The well-trained ROM is then coupled with the structure equation at a specific velocity, the Limit-Cycle Oscillation(LCO) of stall flutter under this flow condition is predicted precisely and more quickly. In order to predict both the critical flutter velocity and LCO amplitudes after bifurcation at different velocities, a new ROM with GRU neural network considering the variation of flow velocities is developed. The stall flutter results predicted by ROM agree well with the CFD ones at different velocities. Finally, a brief sensitivity analysis of two structural parameters of ROM is carried out. It infers the potential of the presented modeling method to depict the nonlinearity of dynamic stall and stall flutter phenomenon.
基金supported by the National Key R&D program of China(Nos.2019YFC0214800 and 2018YFC0213805)the National Natural Science Foundation of China(No.41907190)Shanghai Science and Technology Commission Scientific Research Project(No.19DZ1205006)。
文摘Designing effective control policy requires accurate quantification of the relationship between the ambient concentrations of O3and PM2.5and the emissions of their precursors.However,the challenge is that precursor reduction does not necessarily lead to decreases in the concentrations of O3and PM2.5,which are formed by multiple precursors under complex physical and chemical processes;this calls for the development of advanced model technologies to provide accurate predictions of the nonlinear responses of air quality to emissions.Different from the traditional sensitivity analysis and source apportionment methods,the reduced form models(RFMs)based on chemical transport models(CTMs)are able to quantify air quality responses to emissions more accurately and efficiently with lower computational cost.Here we review recent approaches used in RFMs and compare their structures,advantages and disadvantages,performance and applications.In general,RFMs are classified into three types including(1)sensitivity-based models,(2)models with simplified chemistry and physical processes,and(3)statistical models,with considerable differences in principles,characteristics and application ranges.The prediction of nonlinear responses by RFMs enables more in-depth analysis,not only in terms of real-time prediction of concentrations and quantification of human exposure,health impacts and economic damage,but also in optimizing control policies.Notably,data assimilation and emission inventory inversion based on the nonlinear response of concentrations to emissions can also be greatly beneficial to air pollution control management.In future studies,improvement in the performance of CTMs is exceedingly crucial to obtain a more reliable baseline for the prediction of air quality responses.Development of models to determine the air quality response to emissions under varying meteorological conditions is also necessary in the context of future climate changes,which pose great challenges to the quantification of response relationships.Additionally,with rising requirements for fine-scale air quality management,improving the performance of urban-scale simulations is worth considering.In short,accurate predictions of the response of air quality to emissions,though challenging,holds great promise for the present as well as for future scenarios.
文摘The optimisation of earthquake resistance of high buildings by multi-tuned mass dampers was investigated using bionic algorithms. In bionic or evolutionary optimisation studies the properties of parents are crossed and mutated to produce a new generation with slightly different properties. The kids which best satisfy the object of the study, become the parents of the next generation. After a series of generations essential improvements of the object may be observed. Tuned mass dampers are widely used to reduce the impact of dynamic excitations on structures. A single mass system and multi-mass oscillators help to explain the mechanics of the dampers. To apply the bionic optimisation strategy to high buildings with passive tuned mass dampers subject to seismic loading a special beam element has been developed. In addition to the 6 degrees of freedom of a conventional beam element, it has 2 degrees of freedom for the displacements of the dampers. It allows for fast studies of many variants. As central result, efficient designs for damping systems along the height of an edifice are found. The impact on the structure may be reduced essentially by the use of such dampers designed to interact in an optimal way.
基金This work was supported by the National Natural Science Foundation of China(Grant No.12072293)the Project of State Key Laboratory of Traction Power for Southwest Jiaotong University(Grant No.2021TPL-T10)+2 种基金China Scholarship Council(Grant No.202007000115)the Key Scientific Research Fund Project of Sichuan Education Department(Grant No.18ZA0454)the Key Research Program of Xihua University(Grant No.Z1020212).
文摘Fastening failures have frequently been found on China high-speed railway curved tracks in recent years.Thus the influence of fastening failures on high-speed train-track interaction in curved track needs to be analyzed.A train-curved slab track interaction model is built,in which the real shape of the curved rail is considered and modeled with reduced beam model(RBM)and curved beam theory,and the slabs are modeled with four-nodes Kirchhoff-Love plate elements.The present model is validated at first with different traditional models.Then the influence of fastening failure in curved slab track on train-track interaction dynamics is studied.A different number of failed fastenings is assumed to occur at the curved track,and different types of fastening failure including the fatigue fracture of the clip structure and failure of the rail pad are considered.Based on the calculation results,the fatigue fracture of the clip structure has little influence on train-track interaction dynamics.But when rail pad failure happens and its equivalent vertical stiffness and damping are less than one-tenth of its original,the fastening failure seriously affects the high-speed train operation safety,and it must be prevented.
基金supported by the Natural Science Foundation of Shanghai(No.23ZR1429300)Innovation Funds of CNNC(Lingchuang Fund,Contract No.CNNC-LCKY-202234)the Project of the Nuclear Power Technology Innovation Center of Science Technology and Industry(No.HDLCXZX-2023-HD-039-02)。
文摘Accurate and efficient online parameter identification and state estimation are crucial for leveraging digital twin simulations to optimize the operation of near-carbon-free nuclear energy systems.In previous studies,we developed a reactor operation digital twin(RODT).However,non-differentiabilities and discontinuities arise when employing machine learning-based surrogate forward models,challenging traditional gradient-based inverse methods and their variants.This study investigated deterministic and metaheuristic algorithms and developed hybrid algorithms to address these issues.An efficient modular RODT software framework that incorporates these methods into its post-evaluation module is presented for comprehensive comparison.The methods were rigorously assessed based on convergence profiles,stability with respect to noise,and computational performance.The numerical results show that the hybrid KNNLHS algorithm excels in real-time online applications,balancing accuracy and efficiency with a prediction error rate of only 1%and processing times of less than 0.1 s.Contrastingly,algorithms such as FSA,DE,and ADE,although slightly slower(approximately 1 s),demonstrated higher accuracy with a 0.3%relative L_2 error,which advances RODT methodologies to harness machine learning and system modeling for improved reactor monitoring,systematic diagnosis of off-normal events,and lifetime management strategies.The developed modular software and novel optimization methods presented offer pathways to realize the full potential of RODT for transforming energy engineering practices.
基金support of this work by the National Science Foundation (CMMI Award no.1932975)。
文摘A computationally efficient two-surface plasticity model is assessed against crystal plasticity. Focus is laid on the mechanical behavior of magnesium alloys in the presence of ductility-limiting defects, such as voids. The two surfaces separately account for slip and twinning such that the constitutive formulation captures the evolving plastic anisotropy and evolving tension-compression asymmetry. For model identification, a procedure is proposed whereby the initial guess is based on a combination of experimental data and computationally intensive polycrystal calculations from the literature. In drawing direct comparisons with crystal plasticity, of which the proposed model constitutes a heuristically derived reduced-order model, the available crystal plasticity simulations are grouped in two datasets. A calibration set contains minimal data for both pristine and porous material subjected to one loading path. Then the two-surface model is assessed against a broader set of crystal plasticity simulations for voided unit cells under various stress states and two loading orientations. The assessment also includes microstructure evolution(rate of growth of porosity and void distortion). The ability of the two-surface model to capture essential features of crystal plasticity is analyzed along with an evaluation of computational cost. The prospects of using the model in guiding the development of physically sound damage models in Mg alloys are put forth in the context of high-throughput simulations.
基金supported by the National Science and Technology Major Project, China (No. 2017-II-0009-0023)the Aeronautical Science Foundation of China(No. 2020Z039053004)the Fundamental Research Funds for the Central Universities, China (No. 3102019OQD701)
文摘A Reduced Order Model(ROM)based analysis method for turbomachinery cascade coupled mode flutter is presented in this paper.The unsteady aerodynamic model is established by a system identification technique combined with a set of Aerodynamic Influence Coefficients(AIC).Subsequently,the aerodynamic model is encoded into the state space and then coupled with the structural dynamic equations,resulting in a ROM of the cascade aeroelasticity.The cascade flutter can be determined by solving the eigenvalues of the ROM.Bending-torsional coupled mode flutter analysis for the Standard Configuration Eleven(SC11)cascade is used to validate the proposed method.
