"神光-Ⅱ"装置第九路靶场终端光学组件的研制

针对“神光-Ⅱ”装置第九路系统主激光瞄准精度小于等于30μm和大焦斑辐照均匀性优于10％的要求，提出了靶场终端光学组件的设计结构。应用有限元法对组件关键机械元件和ICF靶室整体进行动静态分析，优化了设计参数。同时与聚焦透镜配合进行数值分析列阵透镜，确定了单元数、曲率和厚度以及单元长和宽等参数。经过实验测试，主激光瞄准精度达到28．9μm，大焦斑辐照的形状为1000μm×500μm，均匀性为12．0％。

阵列光栅压缩器的空域特性

引入角度偏差、位移偏差作为拼接光栅系统的物理参数，定义了拼接光栅的孔径函数，利用傅里叶角谱理论研究了高斯脉冲入射拼接光栅压缩器后的远场分布特性。研究表明；出射脉冲仍然是高斯型脉冲，但包络中心发生偏移，偏移量由角度偏差量和光束口径决定；位移偏差引入的相位随着拼接光栅压缩器传递，其对远场焦斑的影响，取决于每片子光栅的非整数倍光栅常数的横向位移偏差和纵向位移偏差的综合作用。通过数值计算得到了各维偏差对阵列光栅压缩器空域特性的影响，计算表明：光栅面外角度偏差（俯仰左右）和条纹平行度偏差都必须控制在1μrad以内，

大气到海洋激光通信信道仿真

详细分析了蓝绿激光穿过大气海洋信道的信道效应和物理特性,利用理论分析和蒙特卡罗模拟方法完成对光信道仿真。介绍了大气海洋激光通信蒙特卡罗模拟方法及计算步骤。研究了不同厚度云层对光束投影面积的展宽,和光脉冲穿过不同深度海水后的空间分布和时域信号波形,讨论了其不同的展宽机理,并对信道的噪声分布进行了分析。发现云层对光脉冲展宽作用在云层厚度500 m时达到饱和,信号能量的随机起伏随海水深度的增加而增大,但能量分布的半峰全宽并不增加,大气海洋的综合信道效应可以用时延滤波器进行建模。

空间激光通信中的分集接收与分集均衡技术

全面对采用空间分集技术和时域Rake接收机分集的带限空间光通信系统的原理进行了模拟和分析，首次在空间激光通信领域提出了综合了分集接收和均衡技术的联合信道均衡器方法，通过计算机仿真分析，研究了不同空间分集方法在非相关空间光开关键控信号下的误比特率，在不同符号间干扰条件下采用rake接收时的误比特率，以及在不同信噪比和不同信道数时采用联合分集均衡的误码率。研究的结果确认联合分集均衡方法能够明显的提高空间光通信系统的性能。

Nd：YAG激光器光栅式扫描预处理的计算模拟与优化分析

采用计算模拟的方法．研究了光栅式扫描预处理的扫描方式以及脉冲能量波动、定位误差对预处理效率的影响。研究发现。脉冲能量波动及其定位误差使预处理效率降低，同时其影响与扫描方式之间存在相互调制作用．因此可以通过选择合适的扫描方式以及扫描间隔来优化预处理流程，提高预处理效率。此外发现，光斑呈等边三角形排列时的预处理效率优于正方形。

Engineering development of the Lancaster flexible bag.

Describes progress in the last 12 months which has established bag designs and fabrication techniques, giving greater confidence in the life and cost of these components. A quarter scale bag is under construction. Extensive tank testing has also established life time bending moment and mooring load envelopes, enabling hull and mooring design to proceed. A computer simulation programme has been used to check tank model results and to establish turbine and generator operating conditions. This has allowed generation and transmission component design to proceed, and suggests a high operating efficiency can be maintained with a simple control regime. Simple solutions in minor areas such as valve design and damage stability control add to the picture of steady progress in establishing the Lancaster Flexible Bag 's feasibility.

Structural and thermodynamic properties of different phases of supercooled liquid water.

Computer simulation results are reported for a realistic polarizable potential model of water in the supercooled region. Three states, corresponding to the low density amorphous ice, high density amorphous ice, and very high density amorphous ice phases are chosen for the analyses. These states are located close to the liquid-liquid coexistence lines already shown to exist for the considered model. Thermodynamic and structural quantities are calculated, in order to characterize the properties of the three phases. The results point out the increasing relevance of the interstitial neighbors, which clearly appear in going from the low to the very high density amorphous phases. The interstitial neighbors are found to be, at the same time, also distant neighbors along the hydrogen bonded network of the molecules. The role of these interstitial neighbors has been discussed in connection with the interpretation of recent neutron scattering measurements. The structural properties of the systems are characterized by looking at the angular distribution of neighboring molecules, volume and face area distribution of the Voronoi polyhedra, and order parameters. The cumulative analysis of all the corresponding results confirms the assumption that a close similarity between the structural arrangement of molecules in the three explored amorphous phases and that of the ice polymorphs I(h), III, and VI exists.

Structure of coexisting liquid phases of supercooled water: analogy with ice polymorphs.

The structural changes occurring in supercooled liquid water upon moving from one coexisting liquid phase to the other have been investigated by computer simulation using a polarizable interaction potential model. The obtained results favorably compare with recent neutron scattering data of high and low density water. In order to assess the physical origin of the observed structural changes, computer simulation of several ice polymorphs has also been carried out. Our results show that there is a strict analogy between the structure of various disordered (supercooled) and ordered (ice) phases of water, suggesting that the occurrence of several different phases of supercooled water is rooted in the same physical origin that is responsible for ice polymorphism.

State estimation schemes for independent component coupled hidden Markov models

Conventional Hidden Markov models generally consist of a Markov chain observed through a linear map corrupted by additive noise. This general class of model has enjoyed a huge and diverse range of applications, for example, speech processing, biomedical signal processing and more recently quantitative finance. However, a lesser known extension of this general class of model is the so-called Factorial Hidden Markov Model (FHMM). FHMMs also have diverse applications, notably in machine learning, artificial intelligence and speech recognition [13, 17]. FHMMs extend the usual class of HMMs, by supposing the partially observed state process is a finite collection of distinct Markov chains, either statistically independent or dependent. There is also considerable current activity in applying collections of partially observed Markov chains to complex action recognition problems, see, for example, [6]. In this article we consider the Maximum Likelihood (ML) parameter estimation problem for FHMMs. Much of the extant literature concerning this problem presents parameter estimation schemes based on full data log-likelihood EM algorithms. This approach can be slow to converge and often imposes heavy demands on computer memory. The latter point is particularly relevant for the class of FHMMs where state space dimensions are relatively large. The contribution in this article is to develop new recursive formulae for a filter-based EM algorithm that can be implemented online. Our new formulae are equivalent ML estimators, however, these formulae are purely recursive and so, significantly reduce numerical complexity and memory requirements. A computer simulation is included to demonstrate the performance of our results. © Taylor & Francis Group, LLC.

Complex study of transport AC loss in various 2G HTS racetrack coils

HTS racetrack coils are becoming important elements of an emerging number of superconducting devices such as generators or motors. In these devices the issue of AC loss is crucial, as performance and cooling power are derived from this quantity. This paper presents a comparative study of transport AC loss in two different types of 2G HTS racetrack coils. In this study, both experimental measurements and computer simulation approaches were employed. All the experiments were performed using classical AC electrical method. The finite-element computer model was used to estimate electromagnetic properties and calculate transport AC loss. The main difference between the characterized coils is covered inside tape architectures. While one coil uses tape based on RABITS magnetic substrate, the second coil uses a non-magnetic tape. Ferromagnetic loss caused by a magnetic substrate is an important issue involved in the total AC loss. As a result, the coil with the magnetic substrate surprised with high AC loss and rather low performance. © 2013 Elsevier B.V. All rights reserved.

Complex study of transport AC loss in various 2G HTS racetrack coils

HTS racetrack coils are becoming important elements of an emerging number of superconducting devices such as generators or motors. In these devices the issue of AC loss is crucial, as performance and cooling power are derived from this quantity. This paper presents a comparative study of transport AC loss in two different types of 2G HTS racetrack coils. In this study, both experimental measurements and computer simulation approaches were employed. All the experiments were performed using classical AC electrical method. The finite-element computer model was used to estimate electromagnetic properties and calculate transport AC loss. The main difference between the characterized coils is covered inside tape architectures. While one coil uses tape based on RABITS magnetic substrate, the second coil uses a non-magnetic tape. Ferromagnetic loss caused by a magnetic substrate is an important issue involved in the total AC loss. As a result, the coil with the magnetic substrate surprised with high AC loss and rather low performance. © 2013 Elsevier B.V. All rights reserved.

Implementation of multi-group cross-section methodology in BGCore MC-depletion code

BGCore is a software package for comprehensive computer simulation of nuclear reactor systems and their fuel cycles. The BGCore interfaces Monte Carlo particles transport code MCNP4C with a SARAF module - an independently developed code for calculating in-core fuel composition and spent fuel emissions following discharge. In BGCore system, depletion coupling methodology is based on the multi-group approach that significantly reduces computation time and allows tracking of large number of nuclides during calculations. In this study, burnup calculation capabilities of BGCore system were validated against well established and verified, computer codes for thermal and fast spectrum lattices. Very good agreement in k eigenvalue and nuclide densities prediction was observed for all cases under consideration. In addition, decay heat prediction capabilities of the BGCore system were benchmarked against the most recent edition of ANS Standard methodology for UO2 fuel decay power prediction in LWRs. It was found that the difference between ANS standard data and that predicted by the BGCore does not exceed 5%.

Bayesian Learning of Noisy Markov Decision Processes

We consider the inverse reinforcement learning problem, that is, the problem of learning from, and then predicting or mimicking a controller based on state/action data. We propose a statistical model for such data, derived from the structure of a Markov decision process. Adopting a Bayesian approach to inference, we show how latent variables of the model can be estimated, and how predictions about actions can be made, in a unified framework. A new Markov chain Monte Carlo (MCMC) sampler is devised for simulation from the posterior distribution. This step includes a parameter expansion step, which is shown to be essential for good convergence properties of the MCMC sampler. As an illustration, the method is applied to learning a human controller.

Modeling mode i fracture of bitumen films

The fracture behavior of thin films of bitumen in double cantilever beam (DCB) specimens was investigated over a wide range of temperature and loading rate conditions using finite-element analysis. The model includes a phenomenological model for the mechanical behavior of bitumen, implemented into a special-purpose finite-element user material subroutine, combined with a cohesive zone model (CZM) for simulating the fracture process. The finite-element model is validated against experimental results from laboratory tests of DCB specimens by comparing measured and predicted load-line deflection histories and fracture energy release rates. Computer simulation results agreed well with experimental data of DCB joints containing bitumen films in terms of peak stress, fracture toughness, and stress-strain history response. The predicted "normalized toughness," G=2h, was found to increase in a power-law manner with effective temperaturecompensated strain rate in the ductile region as previously observed experimentally. In the brittle regime, G=2h is virtually constant. The model successfully captured the ductile and brittle failure behavior of bitumen films in opening mode (tension) for stable crack growth conditions. © 2013 American Society of Civil Engineers.

Behavior learning of a face robot based on the characteristics of human instruction

Computer simulation experiments were performed to examine the effectiveness of OR- and comparative-reinforcement learning algorithms. In the simulation, human rewards were given as +1 and -1. Two models of human instruction that determine which reward is to be given in every step of a human instruction were used. Results show that human instruction may have a possibility of including both model-A and model-B characteristics, and it can be expected that the comparative-reinforcement learning algorithm is more effective for learning by human instructions.