Full six degrees of freedom coupled dynamic simulation of ship collision and grounding accidents

By taking advantage of the user-defined load subroutine (loadud) and the user common subroutine (usercomm) in LS-DYNA, the authors proposed a new coupled approach for simultaneously calculating structural damage and the planar 3DOF ship motions in ship collisions. The coupled procedure aimed at predicting the detailed structural damage together with reasonable global ship motions. This paper extends the method to consider the full 6DOF ship motions; thus, ship collision as well as grounding accidents can be properly handled. This method is particularly useful for design purposes because the detailed ship hull profile is not needed.A traditional ship maneuvering model is used for the in-plane surge, sway and yaw degrees of freedom with a series of nondimensional coefficients determined from experiments. It is assumed that the out-of-plane degrees of freedom are not coupled with the in-plane ship motions, and there is no coupling among roll, pitch and heave motions. The implementation is verified through free decay tests, and the obtained natural periods show good agreement with theoretical results.Several collision and grounding cases are simulated in which a supply vessel crashes into rigid plates with different orientations. The effects of the roll motion, the heave and pitch motions and the full 6DOF motions are studied. The results are compared with those from a 6DOF decoupled method. Ship motions through the proposed method compare reasonably well with SIMO results. It is found that several consecutive impacts may occur in the simulation of one collision case due to the periodic motions. This is not taken into account in the decoupled method, which makes this method unconservative.     

Apoptin原核表达载体的构建及在大肠杆菌中的表达

目的构建Apoptin的原核表达载体,并制备抗原物质Apoptin融合蛋白。方法在获得Apoptin融合基因的基础上,成功构建了Apoptin的高效原核表达载体pET-28a( )-Apoptin,将该质粒转化至大肠杆菌E.coliBL21(DE3)受体菌中,以IPTG对其进行诱导表达,聚丙烯酰胺凝胶电泳分析目的蛋白。结果转化有Apoptin的原核表达载体pET-28a( )-Apoptin的大肠杆菌E.coliBL21(DE3)经IPTG诱导后,经SDS-PAGE分析,在相对分子质量约17 000的位置出现目的蛋白条带,大小与Apoptin融合蛋白一致。结论Apoptin原核表达载体pET-28a( )-Apoptin能够表达出Apoptin融合蛋白,为进一步的Apoptin研究和制备Apoptin抗体奠定了基础。     

NT4-Ant-Shepherdin[79-87]融合基因重组载体的构建

目的设计构建携带NT4-Ant-Shepherdin[79-87]的cDNA融合基因的重组载体,为针对Survivin的靶向治疗奠定基础。方法应用非对称引物/模板法、PCR技术制备NT4-Ant-Shepherdin[79-87]cDNA片断,连接于pGEM-T-Easy载体,经克隆测序、酶切后与PBV220/NT4质粒连接;转化感受态细胞E.coliDH5α,亚克隆获得NT4-Ant-Shepherdin[79-87]融合基因。结果克隆出Ant-Shepherdin[79-87]基因,经酶切及测序证实结果正确;连接PBV220/NT4,经克隆、酶切,琼脂糖凝胶电泳证实获得321bp的NT4-Ant-Shepherdin[79-87]目的基因片断。结论通过分子生物学技术成功构建了携带NT4-Ant-Shepherdin[79-87]融合基因的重组载体,为进一步研究针对Survivin的靶向抗肿瘤作用奠定了基础。     

基于支持向量机回归树的内燃机振动信号趋势预测

针对标准回归树建立在统计分析基础上所存在的缺陷,提出一种基于支持向量机的回归树预测模型。首先,根据原始振动信号趋势序列构建回归树;然后,针对回归树上包含样本数过少的节点,利用支持向量机,建立能够反映重要变量与响应变量之间映射关系的回归模型。仿真结果表明:即便由于设备出现异常,导致振动信号趋势序列出现非平稳、突变情况,该方法也能准确地预测,性能优于标准分析方法,具有一定的工程实用性。     

基于EMD的矢量水声器方位估计算法

对经验模态分解算法(EMD算法)进行深入研究,对其基本原理、基本性质以及存在的问题进行分析。为改善EMD算法在方位估计的精度,减少高频噪声、间断干扰的影响,本文采用Hilbert-Huang变换方法来消除模态混叠现象。实验结果表明,本文提出的基于EMD的矢量水声器方位估计算法,能够有效提高方位估计的精度。     

Application of frequency estimation algorithm based on a single vector sensor in underwater acoustic communication

1 Introduction1 An acoustic vector sensor (AVS) simultaneously measures the acoustic pressure and the components of acoustic particle velocity which render the basis for developing new signal processing methods[1-2]. The higher processing gain can be obta…     

基于三电平逆变器的永磁同步电动机直接转矩控制新方法

在永磁同步电动机数学模型和三电平空间矢量调制法的基础上,提出一种基于三电平逆变器拓扑结构的永磁同步电机直接转矩控制新方法.该方法采用bang-bang控制器对电机进行控制,通过新型合成矢量开关表对固定合成矢量的选取,有效地抑制了三电平逆变器直流侧支撑电容中点电位波动、限制了输出电压变化率dv/dt并降低了开关损耗,同时...     

地铁车辆辅助逆变器的设计与仿真

以地铁车辆用DC1500V/160kVA辅助逆变器为例,阐述了采用IGBT作为主要开关元件的主电路及其控制系统,并利用MATLAB/SIMULINK进行仿真验证其可行性,最后给出了采用电压空间矢量控制的仿真结果。     

基于支持向量机的多传感器船舶火灾探测技术

针对船舶火灾探测误报率高的情况,为提高火灾探测系统的可靠性,提出一种基于支持向量机的多传感器火灾信息融合方法。经过仿真试验证明,通过多传感器探测数据的有效融合,可以大幅提高火灾探测系统的火灾识别率。     

基于HMM-SVR的船舶动力设备故障模式识别与状态预测研究

船舶动力设备因故障监测信号样本少、变化缓慢且数据特征呈非线性,使得设备故障模式的准确识别和状态预测比较难。鉴于此,文章研究了基于隐马尔科夫模型的故障模式识别方法,利用该模型将微弱变化的信号特征转换为变化较大的对数似然概率对故障模式实现有效识别。在此基础上进一步提出基于HMM-SVR的设备状态预测模型,将遗传算法用于支持向量回归模型参数寻优,并结合隐马尔科夫模型,实现对设备状态的预测。对船用柴油机进行仿真,结果表明上述模型具有较高的识别率,能准确预测船舶动力设备的当前状态。