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
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
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
The reduced-order model （ROM） for the two-dimensional supersonic cavity flow based on proper orthogonal decomposition （POD） and Galerkin projection is investigated. Presently, popular ROMs in cavity flows are base...The reduced-order model （ROM） for the two-dimensional supersonic cavity flow based on proper orthogonal decomposition （POD） and Galerkin projection is investigated. Presently, popular ROMs in cavity flows are based on an isentropic assumption, valid only for flows at low or moderate Mach numbers. A new ROM is constructed involving primitive variables of the fully compressible Navier-Stokes （N-S） equations, which is suitable for flows at high Mach numbers. Compared with the direct numerical simulation （DNS） results, the proposed model predicts flow dynamics （e.g., dominant frequency and amplitude） accurately for supersonic cavity flows, and is robust. The comparison between the present transient flow fields and those of the DNS shows that the proposed ROM can capture self-sustained oscillations of a shear layer. In addition, the present model reduction method can be easily extended to other supersonic flows.展开更多
对于熔盐堆全堆高保真流体动力学计算,即使借助超级计算机的并行计算能力在面对快速甚至实时求解的问题仍然面临效率的巨大挑战,引入和采用模型降阶(Reduced Order Modeling,ROM)方法,将能够有效解决这类问题。基于本征正交分解(Proper ...对于熔盐堆全堆高保真流体动力学计算,即使借助超级计算机的并行计算能力在面对快速甚至实时求解的问题仍然面临效率的巨大挑战,引入和采用模型降阶(Reduced Order Modeling,ROM)方法,将能够有效解决这类问题。基于本征正交分解(Proper Orthogonal Decomposition,POD)方法与Galerkin投影法,引入基于有限体积的模型降阶(ROM based on Finite Volume approximation,FV-ROM)方法和上确界稳定模型降阶(ROM with supremizer stabilization,SUP-ROM)方法,针对液态燃料熔盐堆(Liquid Fuel Molten Salt Reactor,LFMSR)层流和湍流瞬态工况开展适用性分析。结果表明:FV-ROM方法在速度误差和计算效率方面占有明显优势,层流和湍流瞬态速度平均L^(2)相对误差低于0.5%和0.6%,且单步长的加速比分别为1500和1000倍左右;相比之下,SUP-ROM方法在压力预测方面表现出显著的优势,层流和湍流瞬态压力平均L^(2)相对误差低至0.20%和0.38%。因此,通过FV-ROM和SUP-ROM两种方法相结合的方式进行熔盐堆流体动力学速度场和压力场预测,能够更加有效地提高流体动力学仿真的效率,并确保瞬态模拟过程计算可靠性和精确度。展开更多
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.
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.
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Project supported by the National Natural Science Foundation of China(Nos.11232011,11402262,11572314,and 11621202)
文摘The reduced-order model （ROM） for the two-dimensional supersonic cavity flow based on proper orthogonal decomposition （POD） and Galerkin projection is investigated. Presently, popular ROMs in cavity flows are based on an isentropic assumption, valid only for flows at low or moderate Mach numbers. A new ROM is constructed involving primitive variables of the fully compressible Navier-Stokes （N-S） equations, which is suitable for flows at high Mach numbers. Compared with the direct numerical simulation （DNS） results, the proposed model predicts flow dynamics （e.g., dominant frequency and amplitude） accurately for supersonic cavity flows, and is robust. The comparison between the present transient flow fields and those of the DNS shows that the proposed ROM can capture self-sustained oscillations of a shear layer. In addition, the present model reduction method can be easily extended to other supersonic flows.
文摘对于熔盐堆全堆高保真流体动力学计算,即使借助超级计算机的并行计算能力在面对快速甚至实时求解的问题仍然面临效率的巨大挑战,引入和采用模型降阶(Reduced Order Modeling,ROM)方法,将能够有效解决这类问题。基于本征正交分解(Proper Orthogonal Decomposition,POD)方法与Galerkin投影法,引入基于有限体积的模型降阶(ROM based on Finite Volume approximation,FV-ROM)方法和上确界稳定模型降阶(ROM with supremizer stabilization,SUP-ROM)方法,针对液态燃料熔盐堆(Liquid Fuel Molten Salt Reactor,LFMSR)层流和湍流瞬态工况开展适用性分析。结果表明:FV-ROM方法在速度误差和计算效率方面占有明显优势,层流和湍流瞬态速度平均L^(2)相对误差低于0.5%和0.6%,且单步长的加速比分别为1500和1000倍左右;相比之下,SUP-ROM方法在压力预测方面表现出显著的优势,层流和湍流瞬态压力平均L^(2)相对误差低至0.20%和0.38%。因此,通过FV-ROM和SUP-ROM两种方法相结合的方式进行熔盐堆流体动力学速度场和压力场预测,能够更加有效地提高流体动力学仿真的效率,并确保瞬态模拟过程计算可靠性和精确度。
