基于小波神经网络的蒸汽发生器动态过程辨识

在核动力蒸汽发生器(SG)运行过程中，其逆动力学效应使其动态特性难以辨识。为提高蒸汽发生器动态特性辨识的效果，提出了基于小波神经网络的蒸汽发生器动态过程辨识的新方法。辨识模型采用串并联型辨识结构，网络训练采用Levenberg Marququardt学习算法（LMBP）。对蒸汽发生器典型运行工况的辨识结果表明，所提出的方法能够正确地辨识蒸汽发生器的动态特性且具有较高的辨识精度。     

BESⅢ系统环境的网络监测模型

为了适应未来BESⅢ复杂的网络结构，保证高能物理实验的正常进行，建立了一个跨平台的，有助于系统管理员监视和管理的BESⅢ网络环境的监控工具势在必行。本模型不仅能监视路由器交换机各端口的流量，也能监视网络环境中各关键设备的性能状态，并向管理员报警和提交报告。简要介绍了该模型的重大意义，理论基础方案的图形信息。     

训练样本的选取对网络性能的影响

神经网络的训练效果相当地依赖于样本的选取，本文介绍三种不同的样本选取方案，并从Ｍｏｎｔｅ Ｃａｒｌｏ实际进行比较研究为探讨这个问题，模拟分析结果表明，虽然三种方法选取的样本分布迥异，但训练后的网络泛化能力都很强，即接近于Ｂａｙｅｓ极限。此外，，网络的泛化能力还依赖于训练样本集的大小。因此，适当地选取训练样本子集不仅使网络有较好的执行结果，还可以减少训练时间。     

OLAM网络对环境样品γ能谱核素活度的计算

基于OLAM网络学习机制及解谱原理,构造了能分析γ能谱中核素活度的网络.为获取单质核素能谱用于网络训练,采用解谱软件所提供的刻度方程模拟核素的特征能谱,并用其训练网络.用训练好的网络计算环境土壤样品中238U、226Ra、232Th、40K、137Cs等核素的活度,并将计算结果与SPAS-G解谱软件计算结果相比较.结果显示,两者的平均相对偏差绝对值为2.24%,表明网络的构造及特征能谱的模拟是成功的.     

人工神经网络在圆管临界热流密度数据处理中的研究

利用人工神经网络理论对均匀加热垂直上升圆管内的临界热流密度(CHF)进行了预测。分别采用进口条件、出口条件以及局部条件假设，利用收集到的6941个CHF实验数据中的一半作为神经网络训练的样本，采用训练成功的网络预测CHF值可得到比常规方法更好的效果，其均方差分别为6．6％、10．39％和21．39％。     

SBS辐射交联对SBS／PA6共混物性能的影响

本文为提高苯乙烯-丁二烯-苯乙烯嵌段共聚物（Styrene—Butadiene—Styrene triblock copolymer，SBS）与尼龙6（PA6）共混物的相容性，利用SBS的辐射交联对其进行辐射改性，赋予共混物更好的性能。SBS在常温空气气氛下^60Coγ，射线辐照至一定剂量发生化学交联，在共混物内形成三维网络结构，使两相间产生强制互容作用。对改性前后共混物微观形貌，流变性能，机械性能及吸水性的分析与表征。结果表明，辐射交联改性增容后SBS／PA6聚合物合金的性能得到明显提高。     

基于卷积神经网络模型的Gd2O3/6061Al中子屏蔽材料的力学性能预测

提出了一种卷积神经网络模型来预测Gd₂O₃/6061Al中子屏蔽材料的力学性能。以Gd₂O₃/6061Al中子屏蔽材料的EBSD微观形貌及其相应的拉伸性能作为数据集来训练及验证卷积神经网络模型。结果表明：使用多个显微图像，不需任何人工图像处理，卷积神经网络可得到良好的训练结果，其性能优于传统的测试方法；卷积神经网络捕捉到晶粒的存在和晶粒的一些统计信息；晶粒数目和晶粒大小之间具有很强的相关性。     

Linux 集群环境下面向对象数据库的性能及其仿真研究

提出了一个廉价的Tier—3区域中心的方案。为了评价Objectivity／DB在这个Tier—3区域中心的性能，建立了一个简单的原形系统，该原形系统能够容易地扩展到一个更大的试用系统。在多个并发作业运行的环境下，对系统和网络性能进行了测试，包括系统和网络的有效利用率，并分析了系统的瓶颈。最后，还对在这样的计算系统中运行的Objectivity／DB进行了仿真研究，并将其结果与测试结果进行了比较。     

基于ARM的嵌入式Linux网络数据传输性能分析

大型高能物理实验数据采集系统普遍采用多级触发结构,各级间用网络将数据发送到更高级别的系统。以太网技术多作为触发数据传输的媒介。为提高系统传输效率,找到系统数据传输的优化方法,本文基于ARM平台,从数据流角度阐述了Linux2.4内核网络数据的接收过程,并结合测得的内核内部数据分析了网络性能变化的具体原因,给出优化系统性能的方向。     

结构参数对铝基泡沫金属屏蔽性能影响研究

金属泡沫材料拥有优良的γ射线屏蔽能力和较低的密度，但影响其屏蔽性能的关键结构参数及作用规律尚不明确，阻碍了该材料屏蔽性能的进一步优化。本文采用蒙特卡罗方法构建了2种最密堆球模型，计算了理想铝基泡沫金属在各结构参数下的屏蔽性能。研究发现，铝基泡沫金属对能量低于0.24 MeV软γ射线屏蔽能力优于铝基块体材料。控制空心球填充率是优化该材料屏蔽性能的主要可操控方式，且在其适合辐射屏蔽能段时材料越轻性能越好。堆球方式是影响材料屏蔽¹³⁷Cs、⁶⁰Co源γ射线性能的最重要参数，实现面心立方最密堆球铝基泡沫金属的制备将弱化其在屏蔽硬γ射线时的劣势。     

基于核电站网络安全的信息流模型

为了准确描述从1E子网流入非1E级子网的核电站网络的信息流动,本文给出了一个基于核电站网络安全的新的信息流模型。该模型引入了将子网密级和客体密级相结合的二维密级函数的概念,利用该函数值来划分安全类,用两个客体的函数值定义信息流策略。经过严格的数学证明,新的信息流模型合理且安全,能较好反映核电站网络的安全要求。     

多道脉冲分析系统的状态机设计

根据一个新型高速多道脉冲分析系统的结构和设计，提出一种全新的控制用状态机模型，并予以实现，以低成本实现了对整个系统的简单、灵活和全面的控制。     

Strengths and weakness of the methodologies for the innovative nuclear systems analysis

At present nuclear energy is in a transition situation. New efforts are being used trying to find the way to build more nuclear power. As the nuclear energy is an inherently multivariable system, the potential judgment at the ends tends to evolve towards multi criteria analysis methodologies trying to analyze innovative nuclear systems for the future. Nuclear energy has been an active energy player starting 50 years ago, and several times big efforts have been used trying to evaluate the potential of future development of nuclear energy depending on future scenarios using multi criteria analysis methods. Without the intention to be performed an assessment about what finally happens in the evolution of nuclear technology, performing only factual comparison and using only data available in the 1950s, in this work is analyzed if multi criteria analysis methods is sufficient to predict the final success of the currently available well-established commercial reactors. The conclusion is that if uncertainties are not included, the classical multi criteria methodologies evaluated could not be used to predict the successful deployment of PWR, BWR and CANDU, with the status of knowledge of 1956, and without including others factors and external non numerical judgment. Uncertainties produce compatible results with the further historical evolution, but if they have to be included with large margins and as a penalty in the figures of merit.     

基于FPGA的高速峰值检测

针对研发数字多道的实际需求,提出了一种基于FPGA的高速峰值检测技术,并且采用ARM+FPGA的架构实现了基于该技术的数字多道系统。通过Modelsim仿真分析了FPGA峰值检测算法的理论,该算法可精确获取高斯信号的最值并获得幅度值。最后通过CZT探测器进行~(241)Am源实测γ射线能谱,实验结果表明该峰值检测算法及数字多道系统设计可准确并且快速获得能谱图。通过合理设置峰值检测算法的高低阈值,可以测试不同基线值的前放信号。     

Optimal artificial neural network architecture selection for performance prediction of compact heat exchanger with the EBaLM-OTR technique

Artificial Neural Networks (ANN) have been used in the past to predict the performance of printed circuit heat exchangers (PCHE) with satisfactory accuracy. Typically published literature has focused on optimizing ANN using a training dataset to train the network and a testing dataset to evaluate it. Although this may produce outputs that agree with experimental results, there is a risk of over-training or over-learning the network rather than generalizing it, which should be the ultimate goal. An over-trained network is able to produce good results with the training dataset but fails when new datasets with subtle changes are introduced. In this paper we present EBaLM-OTR (error back propagation and Levenberg-Marquardt algorithms for over training resilience) technique, which is based on a previously discussed method of selecting neural network architecture that uses a separate validation set to evaluate different network architectures based on mean square error (MSE), and standard deviation of MSE. The method uses k-fold cross validation. Therefore in order to select the optimal architecture for the problem, the dataset is divided into three parts which are used to train, validate and test each network architecture. Then each architecture is evaluated according to their generalization capability and capability to conform to original data. The method proved to be a comprehensive tool in identifying the weaknesses and advantages of different network architectures. The method also highlighted the fact that the architecture with the lowest training error is not always the most generalized and therefore not the optimal. Using the method the testing error achieved was in the order of magnitude of within 10⁻⁵-10⁻³. It was also show that the absolute error achieved by EBaLM-OTR was an order of magnitude better than the lowest error achieved by EBaLM-THP.     

A GPU-based real time high performance computing service in a fast plant system controller prototype for ITER

EURATOM/CIEMAT and the Technical University of Madrid UPM are involved in the development of a FPSC (fast plant system control) prototype for ITER based on PXIe form factor. The FPSC architecture includes a GPU-based real time high performance computing service which has been integrated under EPICS (experimental physics and industrial control system). In this work we present the design of this service and its performance evaluation with respect to other solutions based in multi-core processors. Plasma pre-processing algorithms, illustrative of the type of tasks that could be required for both control and diagnostics, are used during the performance evaluation.     

Data distribution architecture based on standard real time protocol

Data distribution architecture (DDAR) has been designed conforming to new requirements, taking into account the type of data that is going to be generated from experiments in International Thermonuclear Experimental Reactor (ITER). The main goal of this architecture is to implement a system that is able to manage on line all data that is being generated by an experiment, supporting its distribution for: processing, storing, analysing or visualizing. The first objective is to have a distribution architecture that supports long pulse experiments (even hours). The described system is able to distribute, using real time protocol (RTP), stored data or live data generated while the experiment is running. It enables researchers to access data on line instead of waiting for the end of the experiment. Other important objective is scalability, so the presented architecture can easily grow based on actual necessities, simplifying estimation and design tasks. A third important objective is security. In this sense, the architecture is based on standards, so complete security mechanisms can be applied, from secure transmission solutions until elaborated access control policies, and it is full compatible with multi-organization federation systems as PAPI or Shibboleth.     

多功能网络化核数据获取和处理系统

应用网络技术将多个功能不同、相互独立的以PC微机为基础组成的核数据获取和处理子系统有机互联,组成了一种新型的多功能网络化核数据获取和处理系统,探讨了系统的最佳组成模式、工作原理及实现方法,给出了系统在2．5MeV静电加速器上进行团簇特性研究的初步结果。     

Developing architecture for upgrading I&C systems of an operating nuclear power plant using a quality attribute-driven design method

This paper presents the architecture for upgrading the instrumentation and control (I&C) systems of a Korean standard nuclear power plant (KSNP) as an operating nuclear power plant. This paper uses the analysis results of KSNP's I&C systems performed in a previous study. This paper proposes a Preparation–Decision–Design–Assessment (PDDA) process that focuses on quality oriented development, as a cyclical process to develop the architecture. The PDDA was motivated from the practice of architecture-based development used in software engineering fields. In the preparation step of the PDDA, the architecture of digital-based I&C systems was setup for an architectural goal. Single failure criterion and determinism were setup for architectural drivers. In the decision step, defense-in-depth, diversity, redundancy, and independence were determined as architectural tactics to satisfy the single failure criterion, and sequential execution was determined as a tactic to satisfy the determinism. After determining the tactics, the primitive digital-based I&C architecture was determined. In the design step, 17 systems were selected from the KSNP's I&C systems for the upgrade and functionally grouped based on the primitive architecture. The overall architecture was developed to show the deployment of the systems. The detailed architecture of the safety systems was developed by applying a 2-out-of-3 voting logic, and the detailed architecture of the non-safety systems was developed by hot-standby redundancy. While developing the detailed architecture, three ways of signal transmission were determined with proper rationales: hardwire, datalink, and network. In the assessment step, the required network performance, considering the worst-case of data transmission was calculated: the datalink was required by 120 kbps, the safety network by 5 Mbps, and the non-safety network by 60 Mbps. The architecture covered 17 systems out of 22 KSNP's I&C systems. The architecture is implementable with the equipment developed in South Korea. The architecture can be used as a model to upgrade the existing I&C systems in a planned, large-scale, and one-shot manner. A more detailed architecture down to software level will be developed in the future.     

A Timed-Token Based Network for the ITER Poloidal Field Converter Control System

The control system for poloidal field (PF) in ITER is running in a cluster of distributed controller nodes connected by a soft real-time network. The non-functional performance of network communication, such as latency and jitter, plays an important role in the control system. We analyze the essential of network communication for PF converter control system with stringent real-time requirement and identify the feasibility of the conventional time division method at the request of current data size. However, in order to meet the increased demand for communication data size, we present the design of a timed-token based method and its network scheduler. A test scenario involving a cluster of local control cubicles has been set up to verify the method. The test result shows the timed-token method is more competent to the conventional method and more qualify to the networked control system of PF converter. Meanwhile, in other network with similar architecture, implementation of the timed-token method can guarantee real-time performance as well.