共轭梯度法求解双曲传热多宗量反问题

提出双曲传热反问题热物性参数和边界条件多宗量联合反演的一般数值求解模式,考虑了非均质和分布参数的影响,时域上采用时域精细算法进行离散,建立了便于敏度分析的有限元正演模型.由最小二乘原理建立反演模型,应用共轭梯度法进行求解.探讨了时间步长和测量误差对反演结果的影响,并进行了数值验证.     

共轭梯度法求解多宗量瞬态热传导反问题

提出瞬态热传导反问题中热物性参数和边界条件多宗量反演的一般数值求解模式,导出了敏度计算公式,并用共轭梯度法求解,探讨了测点数目、测量误差和变量初值对反演结果的影响,并进行了数值验证.     

用进化策略方法反演二维弹性波动方程的参数

从材料响应的理论合成与实际测量数据相拟合出发,将二维弹性波动方程的参数反演问题归结为非线性多峰函数的最优化问题.全局最优解的求解采用了进化策略法,并同遗传方法的反演结果进行了比较.数值结果表明,用进化策略方法进行参数反演的精度大大高于用遗传方法进行参数反演的精度,进化策略反演是一种良好的非线性反演方法.     

光度曲线反演空间目标形状的发展现状

光度曲线反演空间目标形状和姿态等参数为空间目标监视与识别提供了新的技术途径。首先分析了基于光度曲线反演空间目标信息的必要性,之后通过关注和跟踪国内外最新发展情况,全面总结了目前进行形状反演的3种主流方法的研究现状及优缺点,对3种反演方法进行了比较分析,指出基于非线性滤波技术的形状反演方法是未来的主要发展方向,并分析了3种非线性滤波技术的优缺点。最后针对反演存在的问题,指出了基于改进的实时性更好的粒子滤波算法,融合多种传感器信息反演几何形状和表面材料更为复杂的空间目标是下一步研究发展的主要方向。     

南海北部负跃层环境下海底参数声学反演

利用2015年南海北部声学实验的实验数据,对海底声学参数进行反演。在综合分析声速起伏及海底模型对海底反演影响的基础上,通过选择等效的海水声速剖面和海底模型,改进了多参量联合地声反演方法,使得其不仅能解决反演中的多值性问题,还能适用于负跃层起伏环境下的声学反演。即当用匹配场反演海底声速和用传播损失反演海底衰减时,如果温跃层内有内波等随机起伏,可使用传播路径上平均声速剖面和单层等效海底进行声场计算。反演得到的海底声速和密度结果与海底采样测量符合较好,拟合给出了海底衰减系数随频率的非线性经验关系式。反演结果可为南海北部声传播规律研究与应用提供海底参数。      

舰船辐射噪声贝叶斯方法反演浅海底层结构及地声参数EI北大核心CSCD

针对以舰船辐射噪声为参考声源的浅海海底分层结构及地声参数反演问题,研究了一种基于贝叶斯理论的浅海多层海底地声参数反演方法。反演中以舰船辐射噪声的线谱成分为研究对象,进而采用非线性贝叶斯反演方法反演浅海底层结构、层中声速、声速衰减和密度,并对反演结果的不确定性进行分析。反演结果的最大后验概率估计值和边缘概率分布分别通过拨正模拟退火算法和Metropolis-Hastings采样法在各参数先验区间内计算获得,并根据贝叶斯信息准则确定最佳海底分层结构。海上实验表明:根据该方法反演获得海底分层结构及地声参数,计算得到的声压场与实测舰船辐射噪声传播损失误差不超过10%,反演结果能够准确表征实验海区海底特征。反演结果不确定性分析表明:海底纵波声速、横波声速以及密度的不确定性更小,对声压场变化更加敏感,反演结果更有效、准确。     

用改进的遗传算法和高斯牛顿法联合反演三维地下水流模型参数

遗传算法在处理非线性优化问题时具有较好的全局搜索性能,但在局部搜索时搜索效率不高,解的精度亦不高,高斯牛顿法在处理非线性优化问题时的性质正好和遗传算法相反,利用遗传算法和高斯牛顿法的优点,用改进的遗传算法和高斯牛顿法联合反演地下水数值模型参数.首先用遗传算法求出地下水模型参数的初值,然后利用这组初值用高斯牛顿法进行数值模型参数的反演,并以一非均质各向同性三维承压非稳定流理想模型为例,结合有限元法讨论了用遗传算法和高斯牛顿法联合反演地下水数值模型参数的过程.计算结果表明,联合参数反演方法,具有收敛速度快、解的精度高的特点,在地下水渗流和水资源评价等领域可广泛应用.     

一种基于激光辐照热效应的薄膜参数反演方法

本文研究并建立了一种基于激光辐照热效应的薄膜参数反演方法.首先给出激光辐照薄膜产生温升问题的热传导理论模型,并利用拉普拉斯变换得到了膜层和基底温度场的解析解;然后以膜层和基底的导热系数为反演参数,基于非线性共轭梯度算法给出反演基本原理及流程,并推导得到了反演过程中灵敏度系数的解析表达式;以aluminum,silver,copper和gold四种金属薄膜为例,通过与有限元法的计算结果对比验证了温度场解析解的正确性;最后结合四种金属薄膜进行了参数反演,通过考察分析不同随机噪声等条件下的参数反演结果,验证了本文方法在薄膜参数反演精度与反演效率等方面的有效性.反演结果显示:本文方法具有较高的反演精度和效率,在迭代截止误差为10~(-7)时只需用少于20次迭代就能收敛;在测量数据中加入的随机噪声越小,反演的迭代收敛次数就越少,即使是在迭代初值与反演结果相差较大时,用包含5%随机噪声的测量数据反演也能快速收敛.本文提出的薄膜参数反演方法不仅适用于反演导热系数,也可扩展用于反演膜层反射系数或吸收率等参数,具有一定的适用性.本文方法对于激光加工或激光损伤过程中的参数反演及优化具有一定的指导意义.     

基于优化理论的高频地波雷达海浪参数反演

针对从高频地波雷达海洋回波多普勒谱反演海浪参数的非线性积分方程,采用线性化近似可以转化为线性积分方程,类似于第一类Fredholm积分方程.文中采用数值方法将线性积分方程转化为二次型最优化问题,并采用共轭梯度法来求解.针对海浪参数的非负先验特性,在迭代过程中,加入非负约束项对共轭梯度法进行了改进.在单部雷达和双部雷达情况下进行正演数值模拟,然后用模拟数据添加不同信噪比的随机噪声进行海浪参数反演,无论是单峰海浪谱还是有两个传播方向的双峰谱反演结果均表明了本文提出的算法在不同信噪比下的有效性.     

基于改进非线性拟合的核磁共振T2谱多指数反演

核磁共振T₂谱多指数反演算法是开展复杂体系样品核磁共振(NMR)弛豫研究最重要的数学工具. 常用的T₂谱多指数反演算法一般都是事先给出弛豫时间T₂分布的布点, 然后转化为线性拟合问题进行求解. 在求解的T₂谱较为分散的时候, 反演得到的T₂谱精确度不高, 分辨率较低. 非线性拟合是解决这个问题的有效办法. 本文针对分散T₂谱反演利用非线性拟合时遇到的初值依赖及运算复杂问题, 利用线性回归最小二乘方法, 改进了其中的带非负约束非线性优化模型, 将搜索的反演参数从T₂, f 减少为T₂, 加快了收敛速度, 减少了对初值的依赖, 提高了反演精度, 使算法更加稳健. 通过用改进的Levenberg-Marquardt算法和差分进化算法进行计算机模拟反演及实验数据反演, 验证了改进方法在核磁共振T₂ 谱反演中的有效性.     

Inverse estimation of the pulse parameters of a time-varying laser pulse to obtain desired temperature at the material surface

A proper selection of the pulse parameters is essential to achieve desired temperature at the material surface. This leads to obtain the required metallurgical changes in the surface vicinity when a time-varying laser pulse is used in a heating process such as surface modification. In this paper, the conjugate gradient method (CGM) for parameter estimation is successfully applied to estimate the unknown laser pulse parameters for those purposes during laser heating process. The determination of the pulse parameters is treated as a one-dimensional, transient, non-linear inverse heat conduction problem (IHCP). Based on a sensitivity analysis, the inverse problem is solved as an optimization problem comparing a desired temperature at the surface and a calculated one where the objective function is minimized by CGM. The method has been applied to a test case of a heating process on steel, appropriate pulse parameters and desired temperature distribution can also be returned.     

A scalable framework for the solution of stochastic inverse problems using a sparse grid collocation approach

Experimental evidence suggests that the dynamics of many physical phenomena are significantly affected by the underlying uncertainties associated with variations in properties and fluctuations in operating conditions. Recent developments in stochastic analysis have opened the possibility of realistic modeling of such systems in the presence of multiple sources of uncertainties. These advances raise the possibility of solving the corresponding stochastic inverse problem: the problem of designing/estimating the evolution of a system in the presence of multiple sources of uncertainty given limited information.A scalable, parallel methodology for stochastic inverse/design problems is developed in this article. The representation of the underlying uncertainties and the resultant stochastic dependant variables is performed using a sparse grid collocation methodology. A novel stochastic sensitivity method is introduced based on multiple solutions to deterministic sensitivity problems. The stochastic inverse/design problem is transformed to a deterministic optimization problem in a larger-dimensional space that is subsequently solved using deterministic optimization algorithms. The design framework relies entirely on deterministic direct and sensitivity analysis of the continuum systems, thereby significantly enhancing the range of applicability of the framework for the design in the presence of uncertainty of many other systems usually analyzed with legacy codes. Various illustrative examples with multiple sources of uncertainty including inverse heat conduction problems in random heterogeneous media are provided to showcase the developed framework.     

金属凝固过程界面换热系数的Tikhonov正则化辨识

金属凝固过程中,铸件与铸型间的界面换热系数是数值模拟所必需的边界条件之一.充分考虑非线性瞬态热传导过程测温数据的误差特点,根据Tikhonov正则化理论,构造合适的正则化泛函,利用Arcangeli准则和Morozov偏差原理确定正则参数,采用灵敏度系数和Newton-Raphson迭代法求解该泛函.具体的案例分析表明,该方法克服了热传导反问题的不适定性,能够保证辨识结果的稳定性和精度.与其他方法相比,随着测温误差的增大,该方法具有较高的辨识精度.     

Modelling of thermal conductance during microthermal machining with scanning thermal microscope using an inverse methodology

In this study, a general methodology for determining the thermal conductance between the probe tip and the workpiece during microthermal machining using Scanning Thermal Microscopy (SThM) has been proposed. The processing system was considered as an inverse heat conduction problem with an unknown thermal conductance. Temperature dependence for the material properties and thermal conductance in the analysis of heat conduction is taken into account. The conjugate gradient method is used to solve the inverse problem. Furthermore, this methodology can also be applied to estimate the thermal contact conductance in other transient heat conduction problems, like metal casting process, injection molding process, and electronic circuit systems.     

反传热问题及其在深冷处理传热分析中的应用

深冷处理作为一种新的材料处理工艺,越来越受到人们的关注,目前深冷处理使材料性能提高的机理尤其是与升降温过程的耦合关系等还尚未完全清楚,需开展更深入的研究,而传热分析是此方面研究的基础。反传热分析方法是研究深冷处理传热问题的一种可行方法。较为详细地叙述了反传热问题的定义及其求解方法,介绍了反传热在深冷处理传热分析中的初步应用,并对深冷处理中应用反传热方法存在的问题进行了探讨。     

Application of a Factorial Design Method to Determine the Accuracy of a Solution to an Inverse Heat Conduction Problem

A numerical/experimental inverse procedure was employed to estimate the temperature-dependent thermal conductivity of a solid body in which 1D heat conduction in a top heated cylindrical sample is assumed. The emphasis is focused on the issue of sensitivity of results to selected assumptions made in inverse calculations. It has been found that the accuracy of heat capacity evaluation brings the largest contribution to final errors (up to 74%). Density accounts for one-fourth to one-third of the total error of determination. The failure to ensure unidirectional heat conduction in a sample during an experiment is important only at elevated temperatures.     

Numerical analysis of uncertain temperature field by stochastic finite difference method

Based on the combination of stochastic mathematics and conventional finite difference method,a new numerical computing technique named stochastic finite difference for solving heat conduction problems with random physical parameters,initial and boundary conditions is discussed.Begin with the analysis of steady-state heat conduction problems,difference discrete equations with random parameters are established,and then the computing formulas for the mean value and variance of temperature field are derived by the second-order stochastic parameter perturbation method.Subsequently,the proposed random model and method are extended to the field of transient heat conduction and the new analysis theory of stability applicable to stochastic difference schemes is developed.The layer-by-layer recursive equations for the first two probabilistic moments of the transient temperature field at different time points are quickly obtained and easily solved by programming.Finally,by comparing the results with traditional Monte Carlo simulation,two numerical examples are given to demonstrate the feasibility and effectiveness of the presented method for solving both steady-state and transient heat conduction problems.     

Infrared thermography applied to the resolution of inverse heat conduction problems: recovery of heat line sources and boundary conditions

In this paper we present an application of infrared thermography for inverse heat conduction problems resolution. The approach described in the paper is based on a Boundary Element Method formulation of the transient heat diffusion equation. The inverse problems under investigation concern the time and space reconstruction of unknown boundary conditions or heat line source strength. As there is a lack of information in the system, some additional measurements are necessary to solve the problem. In the examples proposed in this paper the extra information is provided by an infrared scanner. The measurements contained in the infrared pictures are used in the model as a Dirichlet boundary condition or as a special boundary condition prescribing both temperature and heat flux density on the scanned boundary. We present some experimental results concerning line source strength identification and the reconstruction of unknown heat fluxes applied on an out of reach boundary. All the examples presented in this paper are related to 2D transient diffusion. As the inverse problem is ill-posed, time and space regularization techniques are used to stabilize the solution and reduce the sensitivity of the latter to measurement errors.