脉冲爆轰发动机的系统性能分析

采用简化的脉冲爆轰推进装置模型,利用热循环效率分析方法,推导了包含进气道总压恢复系数的热循环效率公式. 并在特定来流条件下,考察了一个爆轰循环中进气道总压恢复系数和燃烧室初始温度对热循环效率和比冲的影响. 研究发现,降低来流总压损失有助于提高热循环效率,而提高燃烧室初始温度能更有效地提高热循环效率. 据此,提出了多级重起爆脉冲爆轰发动机概念,利用在突扩截面上解耦的爆轰波的前导激波去再次压缩工质,进一步提高工质的热力学参数,从而提高脉冲爆轰装置的热循环效率. 推导了此种构型PDE的热循环效率计算公式,并对多级重起爆脉冲爆轰发动机进行了原理性论证. 研究结果表明,多级重起爆方法提高了燃烧室的爆前温度,从而有效地提高脉冲爆轰发动机热循环效率. 最后,关于出口工质的非完全膨胀的情况,做了定性的阐述,认为只有降低工质的出口压力,才能更有效增加工质的出口动能,从而提高热循环效率.      

喷管对水下爆轰气泡形态和压力特征影响的实验研究

针对具有不同类型喷管的爆轰管在水下爆轰中形成的燃气射流问题，搭建了爆轰实验平台，研究了单次爆轰过程中尾部喷管对水下气泡形态与压力特征的影响。采用数字粒子图像测速技术对高速摄影机拍摄得到的气泡脉动图片进行流场可视化分析，得到各喷管工况下的气泡速度场。为了确认爆轰管内是否形成稳定爆轰波，并观察爆轰波在气液两相界面上的透反射特性，爆轰管尾部安装有2个动态压力传感器，同时在距离喷管一定距离处设置一个水下爆炸传感器，以监测水中传播的压力波。结果表明：扩张喷管工况下的气泡脉动过程与直喷管工况基本一致，但扩张喷管提高了燃气射流速度，气泡膨胀体积更大；因为燃气射流的持续性，收敛喷管工况下的气泡脉动过程具有明显差异，气泡膨胀体积较小，但气泡二次脉动时长相较于一次脉动时长衰减更小；扩张喷管提高了气泡脉动强度，扩张喷管工况下的气泡脉动压力与透射冲击波压力远大于直喷管工况下的气泡脉动压力与透射冲击波压力；收敛喷管工况下的气泡脉动压力与透射冲击波压力都较小，但收敛喷管燃气射流的持续性减缓了气泡脉动压力的衰减速度。相比于直喷管，扩张喷管工况下的气泡脉动时间、气泡脉动压力与透射冲击波压力都更大。收敛喷管工况下的气泡...     

激波诱导火焰失稳与爆轰的条件研究

采用九阶WENO和十阶中心差分格式数值求解激波与火焰作用过程,考察了激波强度、火焰尺寸对激波与球形火焰作用过程的影响。结果表明,增大激波强度或火焰尺寸均可在流场中引发爆轰,但激波强度的影响更大,并且其引发的爆轰可使火焰迅速膨胀,放热率提高,从而影响燃烧特性;此外,爆轰波传播过程中会迅速消耗可燃预混气,合并原有的反射激波,并在流场中形成局部高压区,极大地改变流场结构。     

激波与可运动颗粒群相互作用反射与透射机理实验研究

对水平圆柱形激波管内可压缩性气体与颗粒群的相互作用进行了实验研究与理论分析。利用由压力传感器、信号放大器、示波器和计算机组成的压力测量系统对激波与颗粒群作用时的动态压力进行了测量。发现激波管内发生的是一个复杂的过程,包括激波与颗粒群作用时伴随了激波和膨胀波的反射与透射现象、激波和膨胀波与接触面的干涉、以及激波从激波管端壁的反射等现象。当颗粒装载比α=1时,透射激波被直径为6mm的颗粒群衍射并且有膨胀波紧随其后,因此由透射激波引起的第一个压力峰急剧下降。颗粒装载比和颗粒直径影响透射激波的衍射和衰减。     

二元亚跨声速喷管流动

本文求解了收缩比、扩张比和喉部壁面曲率半径均可任意选取的二元拉伐尔喷管的亚跨声速流动。通过算例,对于收缩角和扩张角对喷管流动的影响、喉部附近喷管流动类型的转变以及喷管流动中超声速泡的出现条件和影响因素等进行了讨论。     

矩形凹槽管道中激波传播的数值研究

基于二维Euler方程,结合五阶加权基本无振荡(weighted essentially nonoscillatory,WENO)格式以及自适应网格加密(adaptive mesh refinement,AMR)技术对入射激波在矩形凹槽管道内传播过程进行了数值模拟。数值结果清晰地显示了入射激波传播过程中与多个矩形凹槽作用以及在凹槽内变化的整个过程,且与已有的实验结果吻合较好。另外,结果还揭示了入射激波与单个凹槽作用时,会发生绕射产生膨胀波,还会发生碰撞从而诱导反射激波。膨胀波会导致入射激波压力降低,而反射激波则导致其升高,但膨胀波的影响占主导作用,因而入射激波波阵面强度出现振荡下降。     

秦岭公路隧道2号竖井地应力与岩爆分析

利用水平圆柱形激波管对激波驱动的可压缩性气固两相流进行了试验研究. 利用压电式压力传感器、电荷放大器、示波器及计算机组成的压力信号测试系统, 对激波 与颗粒作用前后的气相参数进行测量及分析. 试验中测得了激波在管中的传播速 度, 波后气流的压力, 反射激波、透射激波的压力和速度等. 分别考察颗粒、装载 比、驱动气源以及入射激波马赫数等因素的差异对气相参数的影响. 试验结果表明: 激波与颗粒群相互作用时, 会产生反射激波和透射激波, 其强度与驱动气源、颗粒大小、颗粒装载比等参数有关; 激波衰减率随着装载比、马赫数的增大而减小. 研究指出, 在颗粒群被激波加速的初始阶段, 颗粒间的弹性碰撞起着重要的作用.     

激波驱动的气固两相流的动态压力测量

利用水平圆柱形激波管对激波驱动的可压缩性气固两相流进行了试验研究.利用压电式压力传感器、电荷放大器、示波器及计算机组成的压力信号测试系统, 对激波与颗粒作用前后的气相参数进行测量及分析. 试验中测得了激波在管中的传播速度, 波后气流的压力, 反射激波、透射激波的压力和速度等. 分别考察颗粒、装载比、驱动气源以及入射激波马赫数等因素的差异对气相参数的影响.试验结果表明: 激波与颗粒群相互作用时, 会产生反射激波和透射激波,其强度与驱动气源、颗粒大小、颗粒装载比等参数有关;激波衰减率随着装载比、马赫数的增大而减小. 研究指出,在颗粒群被激波加速的初始阶段, 颗粒间的弹性碰撞起着重要的作用.      

INTERFACE EVOLUTIONS AND GROWTH PREDICTIONS OF MIXING ZONE ON PREMIXED FLAME INTERFACE DURING RM INSTABILITY 1)

预混火焰界面的RM (Richtmyer-Meshkov)不稳定导致的界面混合区增长过程在自然界和工程实践中十分常见,但化学反应对其增长的影响机理仍不明确,反应性界面混合区增长速率的预测也未见报道, 因此,开展RM不稳定过程中火焰界面演化和混合区预测的研究十分必要.本文采用带单步化学反应的Navier-Stokes方程和高精度数值格式,研究了正弦形预混火焰界面在平面入射激波及其反射激波作用下的RM不稳定过程.结果表明, 在入射激波作用后的阶段,除RM不稳定本身导致的界面演化为"钉-帽"和"泡"形结构外,化学反应一方面以预混火焰传播的方式促进了界面中"泡"结构的增长,另一方面通过与涡结构的复杂相互作用促进了"钉-帽"结构的增长.化学反应活性越强, 火焰界面的"泡" 结构和"钉-帽"结构的增长越快.在第一次反射激波作用后的阶段,化学反应以相同的火焰传播方式对"泡"和"钉-帽"结构产生影响, 两者效应相抵,因而导致反射激波作用后的阶段中界面混合区增长不受化学反应活性的影响.根据以上分析,分别针对入射激波和第一次反射激波作用后的火焰界面混合区增长速率提出了相应的预测模型,为探索反应性RM不稳定过程的理论预测方法提供了有益参考.     

RM不稳定过程中预混火焰界面演化及混合区增长预测

预混火焰界面的RM (Richtmyer-Meshkov)不稳定导致的界面混合区增长过程在自然界和工程实践中十分常见,但化学反应对其增长的影响机理仍不明确,反应性界面混合区增长速率的预测也未见报道, 因此,开展RM不稳定过程中火焰界面演化和混合区预测的研究十分必要.本文采用带单步化学反应的Navier-Stokes方程和高精度数值格式,研究了正弦形预混火焰界面在平面入射激波及其反射激波作用下的RM不稳定过程.结果表明, 在入射激波作用后的阶段,除RM不稳定本身导致的界面演化为"钉-帽"和"泡"形结构外,化学反应一方面以预混火焰传播的方式促进了界面中"泡"结构的增长,另一方面通过与涡结构的复杂相互作用促进了"钉-帽"结构的增长.化学反应活性越强, 火焰界面的"泡" 结构和"钉-帽"结构的增长越快.在第一次反射激波作用后的阶段,化学反应以相同的火焰传播方式对"泡"和"钉-帽"结构产生影响, 两者效应相抵,因而导致反射激波作用后的阶段中界面混合区增长不受化学反应活性的影响.根据以上分析,分别针对入射激波和第一次反射激波作用后的火焰界面混合区增长速率提出了相应的预测模型,为探索反应性RM不稳定过程的理论预测方法提供了有益参考.      

基于神经网络的偏微分方程求解方法研究综述

神经网络作为一种强大的信息处理工具在计算机视觉,生物医学,油气工程领域得到广泛应用,引发多领域技术变革.深度学习网络具有非常强的学习能力,不仅能发现物理规律,还能求解偏微分方程.近年来基于深度学习的偏微分方程求解已是研究新热点.遵循于传统偏微分方程解析解、偏微分方程数值解术语,本文称用神经网络进行偏微分方程求解的方法为...     

Multivariate padé approximation for solving partial differential equations (PDE)

In this paper, numerical solution of partial differential equations (PDEs) is considered by multivariate padé approximations. We applied these method to two examples. First, PDE has been converted to power series by two‐dimensional differential transformation, Then the numerical solution of equation was put into multivariate padé series form. Thus, we obtained numerical solution of PDE. Copyright © 2010 John Wiley & Sons, Ltd.     

The meshless analog equation method: I. Solution of elliptic partial differential equations

A new purely meshless method for solving elliptic partial differential equations (PDEs) is presented. The method is based on the principle of the analog equation of Katsikadelis, hence its name meshless analog equation method (MAEM), which converts the original equation into a simple solvable substitute one of the same order under a fictitious source. The fictitious source is represented by multiquadric radial basis functions (MQ-RBFs). The integration of the analog equation yields new RBFs, which are used to approximate the sought solution. Then inserting the approximate solution into the PDE and boundary conditions (BCs) and collocating at the mesh-free nodal points results in a system of linear equations, which permit the evaluation of the expansion coefficients of the RBFs series. The method exhibits key advantages over other RBF collocation methods as it is highly accurate and the coefficient matrix of the resulting linear equations is always invertible. The accuracy is achieved using optimal values for the shape parameters and the centers of the multiquadrics as well as of the integration constants of the analog equation, which are obtained by minimizing the functional that produces the PDE. Without restricting its generality, the method is illustrated by applying it to the general second order 2D and 3D elliptic PDEs. The studied examples demonstrate the efficiency and high accuracy of the developed method.     

Numerical simulation of shallow water waves based on generalized equal width (GEW) equation by compact local integrated radial basis function method combined with adaptive residual subsampling technique

Nonlinear Dynamics - The shallow water equation based on the generalized equal width (GEW) equation is a PDE that can be classified in the category of hyperbolic PDEs. The current paper concerns...     

Efficient multigrid preconditioners for atmospheric flow simulations at high aspect ratio

Many problems in fluid modelling require the efficient solution of highly anisotropic elliptic partial differential equations (PDEs) in ‘flat’ domains. For example, in numerical weather and climate prediction, an elliptic PDE for the pressure correction has to be solved at every time step in a thin spherical shell representing the global atmosphere. This elliptic solve can be one of the computationally most demanding components in semi‐implicit semi‐Lagrangian time stepping methods, which are very popular as they allow for larger model time steps and better overall performance. With increasing model resolution, algorithmically efficient and scalable algorithms are essential to run the code under tight operational time constraints. We discuss the theory and practical application of bespoke geometric multigrid preconditioners for equations of this type. The algorithms deal with the strong anisotropy in the vertical direction by using the tensor‐product approach originally analysed by Börm and Hiptmair [Numer. Algorithms, 26/3 (2001), pp. 219–234]. We extend the analysis to three dimensions under slightly weakened assumptions and numerically demonstrate its efficiency for the solution of the elliptic PDE for the global pressure correction in atmospheric forecast models. For this, we compare the performance of different multigrid preconditioners on a tensor‐product grid with a semi‐structured and quasi‐uniform horizontal mesh and a one‐dimensional vertical grid. The code is implemented in the Distributed and Unified Numerics Environment, which provides an easy‐to‐use and scalable environment for algorithms operating on tensor‐product grids. Parallel scalability of our solvers on up to 20 480 cores is demonstrated on the HECToR supercomputer. Copyright © 2015 John Wiley & Sons, Ltd.     

Pulses in binary wave guide arrays and long wave PDE approximations

Binary waveguide arrays are linear arrays of optical waveguides with binary alternation of parameters, and have been of recent interest. They can be modeled by systems of nonlinear ODEs with forms related to the discrete nonlinear Schrödinger equation. Such equations can also arise in semi-classical molecular models of polymers with excitable states in each monomer, and coupling between these.An important class of solutions arises from an initially highly localized signal, such as input to a single element of the array. Simulations show that for a wide array of parameter values and of such initial data, a pulse is generated that travels approximately as a traveling wave. After a suitable phase shift in the variables, this pulse quickly develops a slow spatial variation, leading to a long-wave approximation by a system of coupled third order PDEs; one each for nodes of even and odd indices.This system of PDEs is presented, and verified to quite accurately reproduce the pulse propagation seen in the ODE system; further there is often a strong tendency for the behavior of the two PDE components to converge, with a corresponding convergence of the even and odd index parts of the ODE system solution. The PDE model gives some indication of why this occurs.     

Geometry of Heteroclinic Cascades in Scalar Parabolic Differential Equations

We investigate the geometrical properties of the attractor for semilinear scalar parabolic PDEs on a bounded interval with Neumann boundary conditions. Using the nodal properties of the stationary solutions which are determined by an ordinary boundary value problem, we obtain crucial information about the long-time behavior for the full PDE. Especially, we prove an exact criterion for the intersection of strong-stable and strong-unstable manifolds in the finite dimensional Morse-Smale flow on the attractor.     

Thermal degradation of two liquid fuels and detonation tests for pulse detonation engine studies

The use of liquid fuels such as kerosene is of interest for the pulse detonation engine (PDE). Within this context, the aim of this work, which is a preliminary study, was to show the feasibility to initiate a detonation in air with liquid-fuel pyrolysis products, using energies and dimensions of test facility similars to those of PDEs. Therefore, two liquids fuels have been compared, JP10, which is a synthesis fuel generally used in the field of missile applications, and decane, which is one of the major components of standard kerosenes (F-34, Jet A1, ...). The thermal degradation of these fuels was studied with two pyrolysis processes, a batch reactor and a flow reactor. The temperatures varied from 600°C to 1,000°C and residence times for the batch reactor and the flow reactor were, respectively, between 10–30 s and 0.1–2 s. Subsequently, the detonability of synthetic gaseous mixtures, which was a schematisation of the decomposition state after the pyrolysis process, has been studied. The detonability study, regarding nitrogen dilution and equivalence ratio, was investigated in a 50 mm-diameter, 2.5 m-long detonation tube. These dimensions are compatible with applications in the aircraft industry and, more particularly, in PDEs. Therefore, JP10 and decane were compared to choose the best candidate for liquid-fuel PDE studies. This paper was based on work that was presented at the 20th International Colloquium on the Dynamics of Explosions and Reactive Systems, Montreal, Canada, July 31 – August 5, 2005.     

Neural network as a function approximator and its application in solving differential equations

A neural network(NN) is a powerful tool for approximating bounded continuous functions in machine learning. The NN provides a framework for numerically solving ordinary differential equations(ODEs) and partial differential equations(PDEs)combined with the automatic differentiation(AD) technique. In this work, we explore the use of NN for the function approximation and propose a universal solver for ODEs and PDEs. The solver is tested for initial value problems and boundary value problems of ODEs, and the results exhibit high accuracy for not only the unknown functions but also their derivatives. The same strategy can be used to construct a PDE solver based on collocation points instead of a mesh, which is tested with the Burgers equation and the heat equation(i.e., the Laplace equation).