基于NSGA2与FIuent耦合的分析方法翼型优化

将分析方法引入飞行器气动优化设计,在FIuent软件中进行二次开发,编写了计算熵产率的UDF,来阐述分析方法在气动优化中的作用。以二维翼型为例,通过NURBS曲线进行翼型参数化建模,将NSGA2优化算法与CFD计算耦合起来,计算低雷诺数、5°攻角下的翼型升阻比和熵产率,得到最大升阻比和最小熵产率不断调和的翼型的Pareto解。结果显示,与基准翼型相比,在升阻比提高的条件下,流场熵产率减少,能量效率提高。而且优化翼型的熵产率随着升阻比的增加而增大。     

基于NSGA2与Fluent耦合的分析方法翼型优化

将分析方法引入飞行器气动优化设计,在Fluent软件中进行二次开发,编写了计算熵产率的UDF,来阐述分析方法在气动优化中的作用。以二维翼型为例,通过NURBS曲线进行翼型参数化建模,将NSGA2优化算法与CFD计算耦合起来,计算低雷诺数、5°攻角下的翼型升阻比和熵产率,得到最大升阻比和最小熵产率不断调和的翼型的Pareto解。结果显示,与基准翼型相比,在升阻比提高的条件下,流场熵产率减少,能量效率提高。而且优化翼型的熵产率随着升阻比的增加而增大。     

基于遗传算法的B样条曲线拟合改进算法

B样条曲线拟合应用于绘制离散数据点的变化趋势,一般采用数据逼近或者迭代的方法得到,是图像处理和逆向工程中的重要内容。针对待拟合曲线存在多峰值、尖点、间断等问题,提出一种基于遗传算法的B样条曲线拟合算法。首先利用惩罚函数将带约束的曲线优化问题转换为无约束问题,然后利用改进的遗传算法来选择合适的适应度函数,再结合模拟退火算法自适应调整节点的数量和位置,在寻优的过程中找到最优的节点向量,持续迭代直到产生最终的优良重建曲线为止。实验结果表明,该算法有效地提高了精度并加快了收敛速度。     

混沌蚂蚁群优化求解自由节点B样条曲线拟合

B样条曲线拟合问题中,将节点作为自由变量可大幅提高拟合精度,但这就使曲线拟合问题转化为求解困难的连续多峰值、多变量非线性优化问题,当待拟合的曲线是不连续、有尖点情况,就更为困难。针对这一问题,基于混沌蚂蚁群优化算法CASO,提出了一种新的B样条曲线拟合算法CASO-DF。该算法结合B样条曲线拟合原理,通过蚁群中蚂蚁个体的混沌行为,调整自由节点位置,通过蚁群的自组织行为自适应地调整内部节点数目,解决了B样条曲线拟合问题。仿真结果表明了CASO-DF算法能够有效实现自由节点B样条曲线拟合,且性能优于其他同类算法。     

基于遗传算法的B样条曲线在气象探测中的应用

针对高空气象探测数据变化规律复杂、突变情况不可预测、数据量大等特点,采用基于遗传算法确定节点矢量的B样条曲线拟合方法,并提出优化染色体的产生方式,加速算法的收敛效率,实现了在给定误差要求下,用较少控制点的B样条曲线拟合高空气象探测数据曲线,并通过对气温－高度曲线特征点的拟合效果证明了算法的可行性。     

基于自适应遗传算法的B样条曲线拟合的参数优化

在B样条曲线的最小二乘拟合平面有序数据问题中,经常采用遗传算法进行优化。但随机选取初始种群的遗传算法,容易使得结果陷入局部最优。要达到较高的拟合精度,则需要增加更多的控制顶点。为克服这一缺点,提出了一种自适应的遗传算法对B样条曲线的参数优化。用平均有序数据参数法,将数据参数和节点建立关联,极大提高初始种群的平均适应度;通过优化遗传策略,加快种群进化。实验表明,该算法能用最少的控制顶点和进化代数进行B样条曲线的拟合,得到的拟合曲线逼近效果更好。     

Bézier样条曲线改进的近似弧长参数化方法

提出了Bézier样条曲线利用分割技术近似弧长参数化的一种方法,并给出了相应的算法。通过求出曲线上所谓的‘最坏点’并在相应点处进行分割,可得到两条Bézier样条曲线。让这两条Bézier样条曲线具有与它们的近似弧长成比例的权,并对所得到的新的Bézier样条曲线进行同样的工作最终可得到一条由多条Bézier样条曲线所构成的新曲线。将这多条Bézier样条曲线合并成为一条Bézier样条曲线并通过节点插入技术将所得Bézier样条曲线转化为B-样条曲线的形式可得到全局参数域,其中各条Bézier曲线在全局参数域中所占子区间的长度与它们的权成比例,这样便得到了一条近似弧长参数化曲线。     

无序B样条曲线的曲面拟合算法

针对目前无序曲线拟合算法不能控制拟合误差的问题,提出了利用B样条曲面拟合4条边界线及一组无序B样条曲线的算法.首先由边界曲线得到初始曲面,并将曲线曲面写成分段Bezier形式;然后借鉴曲面蒙皮的思想,得到关于待拟合曲面的方程组,并对相邻的Bézier曲面施加C1连续约束;接着利用SVD以及能量优化来求得唯一的拟合曲面;最后在曲线曲面距离最大处插入节点,重复求解过程,直到误差满足要求.实验结果表明,与已有算法相比,该算法可以得到满足用户误差要求的、光滑的拟合曲面,且具有更好的数值稳定性.     

基于二次B样条曲线拟合的新算法

针对由四点拟合成一条三次B样条曲线过程中计算量大的缺点,提出了一种简单的二次B样条曲线拟合算法。即用两条二次B样条曲线近似一条三次B样条曲线,以期达到计算量小,光滑度也达到要求,提高B样条曲线的绘制速度。     

Bézier样条曲线的近似弧长参数化方法

提出了Bézier样条曲线近似弧长参数化的方法及相应的算法.通过求出曲线近似二分之一弧长的点及其相应的参数值,可将曲线分割为两条Bézier样条曲线.这两条曲线的弧长近似相等,因此让它们带有相同的权1.对新生成的Bézier样条曲线不断重复上述工作,最终得到一条由多条Bézier样条曲线所构成的新的曲线.将这多条Bézier样条曲线合并为一条Bézier样条曲线,进而通过节点插入技术将其转化为B样条形式的曲线以便得到全局参数,其中各段Bézier曲线在全局参数域中所占子区间的长度与它们所具有的权成比例,这样便得到一条近似弧长参数化曲线.     

Analysis-suitable volume parameterization of multi-block computational domain in isogeometric applications

Parameterization of the computational domain is a key step in isogeometric analysis just as mesh generation is in finite element analysis. In this paper, we study the volume parameterization problem of the multi-block computational domain in an isogeometric version, i.e., how to generate analysis-suitable parameterization of the multi-block computational domain bounded by B-spline surfaces. Firstly, we show how to find good volume parameterization of the single-block computational domain by solving a constraint optimization problem, in which the constraint condition is the injectivity sufficient conditions of B-spline volume parameterization, and the optimization term is the minimization of quadratic energy functions related to the first and second derivatives of B-spline volume parameterization. By using this method, the resulting volume parameterization has no self-intersections, and the isoparametric structure has good uniformity and orthogonality. Then we extend this method to the multi-block case, in which the continuity condition between the neighbor B-spline volumes should be added to the constraint term. The effectiveness of the proposed method is illustrated by several examples based on the three-dimensional heat conduction problem.     

Control point adjustment for B-spline curve approximation

Pottmann et al. propose an iterative optimization scheme for approximating a target curve with a B-spline curve based on square distance minimization, or SDM. The main advantage of SDM is that it does not need a parameterization of data points on the target curve. Starting with an initial B-spline curve, this scheme makes an active B-spline curve converge faster towards the target curve and produces a better approximating B-spline curve than existing methods relying on data point parameterization. However, SDM is sensitive to the initial B-spline curve due to its local nature of optimization. To address this, we integrate SDM with procedures for automatically adjusting both the number and locations of the control points of the active spline curve. This leads to a method that is more robust and applicable than SDM used alone. Furthermore, it is observed that the most time consuming part of SDM is the repeated computation of the foot-point on the target curve of a sample point on the active B-spline curve. In our implementation, we speed up the foot-point computation by pre-computing the distance field of the target curve using the Fast Marching Method. Experimental examples are presented to demonstrate the effectiveness of our method. Problems for further research are discussed.     

带两个参数的非均匀三次三角B样条曲线

为了使构造的三次三角非均匀 B-样条曲线在具备形状可调性、高阶连续性、精确 表示椭圆等性质的同时还具有变差缩减性,构造了一类具有全正性的带 2 个参数的非均匀三次 三角 B-样条基函数,进而进行曲线构造。首先假设待构造的非均匀三次三角 B-样条基在每一个 节点处具有 C2连续且具有单位性,进而确定基函数的表达式;然后给出了基函数具有全正性等 重要性质;最后给出了非均匀三次三角 B-样条曲线的定义,并证明了其具有变差缩减性等重要 性质,还证明了曲线在取特殊参数值时具有 C(2n–1)阶连续。实例表明,本文构造的曲线有效解 决了传统方法存在的问题,适合于几何设计。     

高阶连续的形状可调三角多项式曲线曲面

目的目前使用的B样条曲线曲面存在着高连续阶与高局部调整性两者无法兼而有之的不足,且B样条曲线曲面的形状被控制顶点和节点向量唯一确定,这些因素影响着B样条方法的几何设计效果与方便性。本文旨在克服这种局限,以期构造具有高次B样条方法的高连续阶,低次B样条方法的高局部调整性,以及有理B样条方法权因子决定的形状调整性的曲线曲面。方法在三角函数空间上构造了一组含参数的调配函数,进而定义具有与3次B样条曲线曲面相同结构的新曲线与张量积曲面。结果新曲线曲面继承了B样条方法的凸包性、对称性、几何不变性等诸多性质。不同的是,同样是基于4点分段,3次均匀B样条曲线C2连续,而对于等距节点,在一般情况下,新曲线C5连续,当参数取特殊值时可达C7连续。新曲线在C5连续的情况下存在1个形状参数,能较好地调整曲线的形状同时又无须改变控制顶点。另外,将形状参数设为特定值,新曲线可以自动插值给定点列。新曲面具有与新曲线相应的优点。结论在强局部性下实现高阶连续性的形状可调分段组合曲线曲面,为高阶光滑曲线曲面的设计提供了可能,并且新曲线实现了逼近与插值的统一表示,能较好地应用于工程实际。调配函数的构造方法具有一般性,可用相同方式构造其他具有类似性质的调配函数。     

Iteration and optimization scheme for the reconstruction of 3D surfaces based on non-uniform rational B-splines

Curve or surface reconstruction is a challenging problem in the fields of engineering design, virtual reality, film making and data visualization. Non-uniform rational B-spline (NURBS) fitting has been applied to curve and surface reconstruction for many years because it is a flexible method and can be used to build many complex mathematical models, unlike certain other methods. To apply NURBS fitting, there are two major difficult sub-problems that must be solved: (1) the determination of a knot vector and (2) the computation of weights and the parameterization of data points. These two problems are quite challenging and determine the effectiveness of the overall NURBS fit. In this study, we propose a new method, which is a combination of a hybrid optimization algorithm and an iterative scheme (with the acronym HOAAI), to address these difficulties. The novelties of our proposed method are the following: (1) it introduces a projected optimization algorithm for optimizing the weights and the parameterization of the data points, (2) it provides an iterative scheme to determine the knot vectors, which is based on the calculated point parameterization, and (3) it proposes the boundary-determined parameterization and the partition-based parameterization for unorganized points. We conduct numerical experiments to measure the performance of the proposed HOAAI with six test problems, including a complicated curve, twisted and singular surfaces, unorganized data points and, most importantly, real measured data points from the Mashan Pumped Storage Power Station in China. The simulation results show that the proposed HOAAI is very fast, effective and robust against noise. Furthermore, a comparison with other approaches indicates that the HOAAI is competitive in terms of both accuracy and runtime costs.     

基于遗传算法的B样条曲线和Bézier曲线的最小二乘拟合

考虑用B样条曲线拟合平面有序数据使得最小二乘拟合误差最小.一般有两种考虑,一种是保持B样条基函数的节点不变,选择参数使得拟合较优.参数的选择方法包括均匀取值、累加弦长法、centripetal model、Gauss-Newton迭代法等.另一种则是先确定好参数值(一般用累加弦长法),然后再用.某一算法计算出节点,使得拟合较优.同时把两者统一考虑,用遗传算法同时求出参数、节点使得拟合在最小二乘误差意义下最优.与Gauss-Newton迭代法、Piegl算法相比,本方法具有较好的鲁棒性(拟合曲线与初始值无关)、较高的精度及控制顶点少等优点.实验结果说明采用遗传算法得到的曲线逼近效果更好.用遗传算法对Bezier曲线拟合平面有序数据也进行了研究.     

三次B样条曲线骨架卷积曲面造型

提出一种基于B样条曲线降阶的三次B样条曲线骨架卷积曲面造型方法．首先通过顶点扰动降阶方法把三次B样条曲线骨架（C^1连续）降阶为C^1连续的二次B样条，然后应用二次B样条曲线骨架的卷积曲面势函数计算方法得到三次B样条曲线骨架的势函数．     

Parameterization of computational domain in isogeometric analysis: Methods and comparison

Parameterization of computational domain plays an important role in isogeometric analysis as mesh generation in finite element analysis. In this paper, we investigate this problem in the 2D case, i.e., how to parametrize the computational domains by planar B-spline surface from the given CAD objects (four boundary planar B-spline curves). Firstly, two kinds of sufficient conditions for injective B-spline parameterization are derived with respect to the control points. Then we show how to find good parameterization of computational domain by solving a constraint optimization problem, in which the constraint condition is the injectivity sufficient conditions of planar B-spline parameterization, and the optimization term is the minimization of quadratic energy functions related to the first and second derivatives of planar B-spline parameterization. By using this method, the resulted parameterization has no self-intersections, and the isoparametric net has good uniformity and orthogonality. After introducing a posteriori error estimation for isogeometric analysis, we propose r-refinement method to optimize the parameterization by repositioning the inner control points such that the estimated error is minimized. Several examples are tested on isogeometric heat conduction problem to show the effectiveness of the proposed methods and the impact of the parameterization on the quality of the approximation solution. Comparison examples with known exact solutions are also presented.     

三次NURBS曲线的插值方法

本文提出了一个用于3次NURBS曲线插值的新方法,该方法首先用二次规划算出控制顶点的权因子,然后反算出所有的控制顶点,它能确保由型值点的权W_i(>0)所算出的控制顶点的权也均大于0,插值曲线具有C~2连续性,当W_i均为一个大于0的常数时,插值曲线退化为非均匀B样条曲线。     

曲线曲面逼近与插值的统一表示

为了用一种模型实现从逼近到插值的转换,在多项式空间上构造了含一个参数的调配函数,由之定义了基于4点分段的曲线,该曲线可以理解为由相同的一组控制顶点定义的逼近曲线和插值曲线的线性组合,其中的逼近曲线为3次均匀B样条曲线,插值曲线经过除首末点以外的所有控制点。在均匀参数分割下,曲线具有C2连续性,取特殊参数时可达C3连续。在参数变化过程中,曲线各段起点、终点的位置发生改变,但这些点处的一阶、二阶导矢始终保持不变,即始终与3次B样条曲线相同。曲线形状与端点条件密切相关,而B样条曲线具有良好的保形性,这些综合因素使得曲线在形状变化的过程中始终可以较好地保持控制多边形的特征。采用张量积方法将曲线推广至曲面,曲线曲面图例显示了该方法在造型设计中的有效性。