Some experimental studies on angle effect in penetration

This investigation describes and analyses the experimental results pertinent to the penetration of Al-7017 plates with non-deformable steel projectiles at a velocity of 840 ± 15 m/s at different angles of impact. The results include the variation in damage pattern, damage area at front and back, mid penetration channel observations, residual velocity and energy absorption capacities at different obliquities. Some observations relating to the adiabatic shear bands formation have also been presented. The micro hardness values along the path of penetration have been studied in order to understand the increase in energy absorption at oblique impact. The experimental data shows a transition of failure mode from an adiabatic shear band induced shear plugging at lower obliquities to a more homogeneous deformation of the target material and gouging at higher obliquities.     

用流动孔隙测量术设计复合型过滤介质

为使过滤材料在使用中达到令人满意的性能 ,要求过滤介质具有适宜的孔径尺寸、孔径分布、孔体积、孔表面积及渗透性。在本项调研中 ,将过滤介质用流动孔隙测量术进行了特征化处理 ,然后用预先特征化处理过的过滤介质设计复合型过滤介质 ,并用流动孔隙测量术测试复合型过滤介质。测量并分析通过干样品和湿样品的气体压力和流量 ,由此得出最大孔径尺寸、孔径分布及渗透性。数据表明 ,具有独特特征的复合型过滤介质可以通过合理挑选预先特征化处理过的过滤介质来制备。     

An improved differential evolution trained neural network scheme for nonlinear system identification

This paper presents an improved nonlinear system identification scheme using di？erential evolution （DE）, neural network （NN） and Levenberg Marquardt algorithm （LM）. With a view to achieve better convergence of NN weights optimization during the training, the DE and LM are used in a combined framework to train the NN. We present the convergence analysis of the DE and demonstrate the efficacy of the proposed improved system identification algorithm by exploiting the combined DE and LM training of the NN and suitably implementing it together with other system identification methods, namely NN and DE＋NN on a number of examples including a practical case study. The identification results obtained through a series of simulation studies of these methods on different nonlinear systems demonstrate that the proposed DE and LM trained NN approach to nonlinear system identification can yield better identification results in terms of time of convergence and less identification error.     

A differential evolution based neural network approach to nonlinear system identification

This paper addresses the effectiveness of soft computing approaches such as evolutionary computation (EC) and neural network (NN) to system identification of nonlinear systems. In this work, two evolutionary computing approaches namely differential evolution (DE) and opposition based differential evolution (ODE) combined with Levenberg Marquardt algorithm have been considered for training the feed-forward neural network applied for nonlinear system identification. Results obtained envisage that the proposed combined opposition based differential evolution neural network (ODE-NN) approach to identification of nonlinear system exhibits better model identification accuracy compared to differential evolution neural network (DE-NN) approach. The above method is finally tested on a one degree of freedom (1DOF) highly nonlinear twin rotor multi-input–multi-output system (TRMS) to verify the identification performance.     

Study of the neutron-noise transmission characteristics of non-multiplying media in liquid-metal fast breeder reactors using transport theory

The neutron-noise transmission characteristics of non-multiplying media typical to LMFBRs are studied using transport theory and the results are compared with the corresponding results for diffusion theory. In transport theory suitable expressions are derived for the discrete (asymptotic) and continuum (transient) solutions for the frequency-dependent neutron flux. Further, it is examined how the break frequency of the neutron flux APSD, calculated using transport theory and diffusion theory, changes with distance from the neutron-noise source for materials like graphite, stainless steel and borated concrete. The 1-D, isotropic, monoenergetic neutron transport equation for an infinite medium is used.     

Comparative RFLP mapping of a wild rice, Oryza officinalis, and cultivated rice, O. sativa

A comparative RFLP map was constructed in a wild rice, Oryza officinalis, by using 139 genomic and cDNA probes that had been used previously to map RFLPs in O. sativa. Nine of the 12 chromosomes of O. officinalis were highly homosequential to those of O. sativa. A major rearrangement of gene order was detected in chromosome 1 and small inversions were found in chromosomes 3 and 11. Fourteen translocated RFLP markers were found, and chromosome 11 contained a high frequency of such translocated segments. Results were consistent with meiotic and trisomic analysis, which suggested that the genomes of O. officinalis and O. sativa were similar. Applications of comparative maps in plant breeding and gene cloning are discussed.