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Logistic混沌系统的图像加密算法研究

给出了一种基于Logistic混沌系统的快速数字图像加密算法.首先通过给定的密钥序列生成混沌系统的初值,由此初值生成混沌矩阵;然后利用此混沌矩阵与原图像进行按位异或运算得到中间过渡图像;最后再对中间过渡图像作混沌置乱运算和混沌块置乱操作.该算法的优点是不论融合还是置乱均是利用混沌序列进行操作.实验数据表明,该算法简单易行,加密与恢复效果良好,具有较好的安全性.     

基于相关系数的决策树优化算法

通过分析ID3算法的基本原理及其多值偏向问题,提出了一种基于相关系数的决策树优化算法。首先通过引进相关系数对ID3算法进行改进,从而克服其多值偏向问题,然后运用数学中泰勒公式和麦克劳林公式的性质,对信息增益公式进行近似简化。通过具体数据的实例验证,说明优化后的ID3算法能够解决多值偏向问题。标准数据集UCI上的实验结果表明,在构建决策树的过程中,既提高了平均分类准确率,又降低了构建决策树的复杂度,从而还缩短了决策树的生成时间,当数据集中的样本数较大时,优化后的ID3算法的效率得到了明显的提高。     

考虑桩顶水平反力的水平受荷单桩弹塑性解析解

基于线性地基反力法和土体的弹塑性本构关系,对桩顶水平反力系数不为零时的水平受荷桩进行了研究,给出了桩顶土屈服临界荷载（水平力、弯矩）的耦合关系式。研究结果表明,当荷载大于临界荷载时,桩顶土发生塑性屈服,其塑性屈服深度随荷载的增加而增加,但其塑性区扩展速率随桩顶荷载的增加而逐渐减小。给出了弹性区与塑性区桩内力耦合的矩阵方程及其迭代求解格式;利用曲面拟合软件给出了塑性区换算深的计算公式。通过工程算例验证,证明该方法可靠快捷,便于手算,值得推广。      

Safe Autonomous Agent Formation Operations Via Obstacle Collision Avoidance

In this paper, we consider the problem of flocking and shape‐orientation control of multi‐agent systems with inter‐agent and obstacle collision avoidance. We first consider the problem of forcing a set of autonomous agents to form a desired formation shape and orientation while avoiding inter‐agent collision and collision with convex obstacles, and following a trajectory known to only one of the agents, namely the leader of the formation. Then we build upon the solution given to this problem and solve the problem of guaranteeing obstacle collision avoidance by changing the size and the orientation of the formation. Changing the size and the orientation of the formation is helpful when the agents want to go through a narrow passage while the existing size or orientation of the formation does not allow this. We also propose collision avoidance algorithms that temporarily change the shape of the formation to avoid collision with stationary or moving nonconvex obstacles. Simulation results are presented to show the performance of the proposed control laws.     

压力和温度对瓦斯扩散规律的影响研究

针对瓦斯吸附解吸法测定瓦斯扩散系数时局限于颗粒煤、无法施加围压且气体压力不能任意设定等问题,采用规则块煤结合气相色谱分析法测定瓦斯在块煤中的扩散系数,分析了不同气体压力、温度下块煤瓦斯扩散规律。实验结果表明,随着气体压力的增大,煤基质吸附气体增加且发生膨胀变形,从而孔隙减小,扩散阻力增大,扩散系数减小;随着温度的升高,气体分子运动速度增大,扩散动力增强,扩散系数变大。     

Almost strictly total positivity of NUAT B-spline basis

Total positivity of spline basis has been well known in the theory of computer aided geometry design, which is highly related with good shape preserving property. Almost strictly total positivity is stronger, which could determine the positive minors while the other is zero. In this paper, a geometrical approach is proposed to prove the collection matrices of NUAT B-spline basis are almost strictly totally positive. In this paper, knot insertion algorithm combined with coefficient variation of NUAT B-spline function, we put forward an intuitive and geometrical method.     

An impulse control approach to dike height optimization

This paper determines the optimal timing of dike heightenings as well as the corresponding optimal dike heightenings to protect against floods. To derive the optimal policy, we design an algorithm based on the Impulse Control Maximum Principle. In this way, this paper presents one of the first real-life applications of the Impulse Control Maximum Principle developed by Blaquière. We show that the proposed impulse control (IC) approach performs better than dynamic programming with respect to computational time. This is caused by the fact that IC does not need discretization in time.     

Global structure constrained local shape prior estimation for medical image segmentation

Organ shape plays an important role in clinical diagnosis, surgical planning and treatment evaluation. Shape modeling is a critical factor affecting the performance of deformable model based segmentation methods for organ shape extraction. In most existing works, shape modeling is completed in the original shape space, with the presence of outliers. In addition, the specificity of the patient was not taken into account. This paper proposes a novel target-oriented shape prior model to deal with these two problems in a unified framework. The proposed method measures the intrinsic similarity between the target shape and the training shapes on an embedded manifold by manifold learning techniques. With this approach, shapes in the training set can be selected according to their intrinsic similarity to the target image. With more accurate shape guidance, an optimized search is performed by a deformable model to minimize an energy functional for image segmentation, which is efficiently achieved by using dynamic programming. Our method has been validated on 2D prostate localization and 3D prostate segmentation in MRI scans. Compared to other existing methods, our proposed method exhibits better performance in both studies.