采用高能电子束辐照技术制造高反压大功率开关晶体管

应用最佳能量为１２ＭｅＶ的电子束对大功率开关晶体管进行了辐照。结果表明，经电子束辐照的开关晶体管具有开关特性优良、热稳定性高、器件参数一致性好等特点。     

HIRFL-CSR电子冷却装置电子枪的参数测试

在用实心电子束对离子进行冷却过程中，束流累积会增强电子离子重组概率和空间电荷效应而引起束流损失。针对这个问题，HIRFL-CSR电子冷却装置采用了一种能够产生从实心到空心电子束且电子束密度连续可调的特殊电子枪设计。本文介绍电子枪的结构及工作特点，给出一些主要参数的实验结果，并通过理论计算分析了用空心电子束进行冷却的优点。      

低能电子束设备与应用

低能电子束是一种先进的底层共性技术，美国、日本及欧洲发达国家从20世纪80年代开始就将该技术广泛应用于各种高科技产品的生产制造过程中。由于进口电子束设备及配套工艺和原材料的价格昂贵，严重制约了低能电子束技术在国内的推广。近年来，国内自主研发低能电子束设备技术的快速进步，降低了下游行业的进入门槛，有力推进了国内企业在新材料、新技术、新工艺上的研究，突破了行业发展瓶颈，使低能电子束及应用迎来快速发展。     

法兰环缝局部真空电子束焊接技术研究

叙述了局部真空电子束焊接的特点及其在国防工业和民用工业的应用前景，叙述了国内外局部真空电子束焊接的发展状况，介绍了自行研制的法兰环缝局部真空电子束焊接装置和它的主要技术指标，以及该设备研制已突破的关键技术。     

慢正电子束研究电子束固化涂层的微观结构

用慢正电子束多普勒展宽谱研究环氧丙烯酸酯体系电子束固化涂层。Ｓ－Ｅ曲线给出了稀释剂分子结构及其相对含量，辐射剂量，预聚物和交联剂含量等对ＥＢＣ涂层 观结构的影响，以及随深度变化的信息。     

10~(11)瓦强流相对论性电子束加速器

本文是我们所研制的10~(11)瓦强流相对论性电子束加速器的总结报告。文章给出了该设备的指标、技术数据、各部份结构及实验结果。我们对整个设备进行了较全面的测试,设计与实测值基本一致。     

试样重组技术应用现状分析

详细介绍了国内外已有的试样重组案例,归纳了电弧焊、电子束焊、激光焊、表面激活焊的工艺流程及特点,对比分析了各焊接方法的优劣势。列举了重组过程中及重组后试样的质量证明方法。介绍试样重组技术在核电工程中的应用,分析了国内开展此项业务的现有条件、与国际先进水平的差距及努力提升的方向。分析表明:电弧焊、电子束焊试样重组应用最为广泛,激光焊适合于各种类型试样的重组。     

强流脉冲电子束纯铝表面改性过程的热力学模拟

针对强流脉冲电子束表面改性的特点,建立了相应的数学物理模型,以纯铝材表面改性实验为基础,计算了由强流脉冲电子束辐照材料表面所产生快速升降温与熔凝过程,对其中的熔化、蒸发、热应力波等现象分别进行了数值模拟。计算结果表明,熔化深度约在1-10μm,与实验结果接近;蒸发作用影响较小,汽化层厚度仅为纳米量级;热应力波的幅值约在0．1MPa量级,且与脉冲的能量密度大致成正比,但是对材料结构和性能有重要影响。     

计算脉冲电子束辐照下能量沉积剖面的新方案

脉冲电子束辐照材料试验研究中,束流电子具有不同的速度和角度分布。但数值模拟计算一般都考虑电子束垂直入射靶材料,这可能导致数值计算结果与试验结果不符。针对该问题,提出了一种计算电子束辐照下能量沉积剖面的新方案,利用MCNP(Monte Carlo N Particle Transport Code)软件对铝、铜、钽金属材料在电子束辐照下的能量沉积进行模拟,分析了电子束垂直入射与带有角度分布入射时能量沉积的差异,为解释电子束辐照试验测量数据与理论计算结果之间的差异提供了依据。     

电子束辐射技术在粘胶工业中的应用

在粘胶纤维的陈化工艺中,纤维素分子的氧化裂解较难控制,而纤维素分子的电子束辐射裂解的优点很明显,介绍了电子束辐射技术在粘胶纤维工业中应用的可行性,并从技术、工艺、经济和环境保护等方面讨论了用电子束辐射技术代替纤维素分子氧化裂解工艺的可行性。介绍了国个电子束技术用于粘胶生产的研究进展。     

合肥光源储存环控制系统

合肥光源储存环控制系统是一个基于EPICS(Experiment Physics and Industrial Control System)的分布式控制系统,本文首先描述其硬件结构、软件设计,然后重点介绍束流慢加速、束流闭轨校正、机器状态在线查询、数据存档及历史数据查询等应用软件的开发。运行结果表明,合肥光源储存环控制系统很好地满足了机器运行和机器研究的需要。     

强流束传输中束晕的形成

放射性洁净核能系统的强流加速器中，绕束核外围的束晕最容易损失在机器壁上，产生超标的放射性，弄清束晕形成的机制，寻找尽量降低束损的加速器设计方法，对于建造这样的强流加速器至关重要。文章人束晕理论 方法等方面进行了综合论述，并在其中给出一些初步研究结果。最后，讨论了束晕研究中尚待解决的课题。     

Chatter suppression methods of a robot machine for ITER vacuum vessel assembly and maintenance

In the process of assembly and maintenance of ITER vacuum vessel (ITER VV), various machining tasks including threading, milling, welding-defects cutting and flexible hose boring are required to be performed from inside of ITER VV by on-site machining tools. Robot machine is a promising option for these tasks, but great chatter (machine vibration) would happen in the machining process. The chatter vibration will deteriorate the robot accuracy and surface quality, and even cause some damages on the end-effector tools and the robot structure itself. This paper introduces two vibration control methods, one is passive and another is active vibration control. For the passive vibration control, a parallel mechanism is presented to increase the stiffness of robot machine; for the active vibration control, a hybrid control method combining feedforward controller and nonlinear feedback controller is introduced for chatter suppression. A dynamic model and its chatter vibration phenomena of a hybrid robot is demonstrated. Simulation results are given based on the proposed hybrid robot machine which is developed for the ITER VV assembly and maintenance.     

Three Dimensional Simulation of ITER Machine by Using Geant4

International Thermonuclear Experimental Reactor (ITER) is used as a model in this examination. By using dimensional characteristics and materials used in this Tokomak and in order to study some of its parameters, simulation is done by the use of Geant4 code. In order that the results are closer to reality, all the volumes (cylinders, torus and spheres) are defined three-dimensional for the code. With respect to neutrons produced in the plasma because the fusion reaction (D, T), for the neutrons with 14.1 MeV energy that emit isotropically, a torus shaped volume source also is defined for the code. The number of neutrons was obtained at any moment of the time in different parts of the machine. For some important parts, neutron energy spectrum in that part also was obtained. X-rays energy spectrum and prompt gamma inside and outside of the machine are also obtained. The results correspond well with published reports of this field. This paper also tries to show the ability and capability of the Geant4 code to simulate nuclear reactors like ITER.     

Completion of the FM-1 Machine

The Princeton Floating Multipole Machine, FM-1, has been assembled, and some tests have been performed. The device contains a 60-inch diameter superconducting ring and will be operated as a spherator. The assembly will be described with several unusual features of this new machine. Details of the unique components are presented in other papers of this conference.     

中国实验快堆换料机控制系统设计及台架调试

换料机是中国实验快堆的换料设备,主要通过抓手和导向管的配合运动,实现堆芯组件的抓取和插放。换料机控制系统采用了可编程控制器、数字直流调速器等自动化电气设备。通过换料综合试验台架调试,控制设备运行稳定、可靠,验证了换料机控制系统的设计满足技术规格书及工艺要求。     

Machine learning application to predict the electron temperature on the J-TEXT tokamak

The reliability of diagnostic systems in tokamak plasma is of great significance for physics researches or fusion reactor. When some diagnostics fail to detect information about the plasma status, such as electron temperature, they can also be obtained by another method: fitted by other diagnostic signals through machine learning. The paper herein is based on a machine learning method to predict electron temperature, in case the diagnostic systems fail to detect plasma temperature. The fully-connected neural network, utilizing back propagation with two hidden layers, is utilized to estimate plasma electron temperature approximately on the J-TEXT. The input parameters consist of soft x-ray emission intensity, electron density, plasma current, loop voltage, and toroidal magnetic field, while the targets are signals of electron temperature from electron cyclotron emission and x-ray imaging crystal spectrometer. Therefore, the temperature profile is reconstructed by other diagnostic signals, and the average errors are within 5%. In addition, generalized regression neural network can also achieve this function to estimate the temperature profile with similar accuracy. Predicting electron temperature by neural network reveals that machine learning can be used as backup means for plasma information so as to enhance the reliability of diagnostics.     

利用变化能谱实现密度解析成像的方法

本文以两种成分的图像分离为例详细地介绍了通过分析不同能量Ｘ射线束所获得的图像来实现分离物体内部各成分图像的基本理论，并给出了实验结果。