共振、混沌与束晕形成

研究强流束中的非线性共振、混沌与束晕形成的关系.给出强流束中非线性共振范围的表达式及其随束流空间电荷效应变化的数值结果和图表曲线,提出由非线性共振而激发的束晕形成的空间电荷效应极限,并分析束晕形成的过程.     

束晕-混沌的非线性反馈离散控制

 基于非线性控制方法，提出了一种特殊的非线性反馈函数， 即小波反馈函数，用于离散控制强流质子束的束晕 混沌。控制后质子束的束晕强度因子很快趋于零，束均方根半径、束横向平均发射度等都减至控制前的三分之一稍多, 证明该控制方法切实有效，在工业上具有实用价值。     

小波函数反馈法实现对强流束晕混沌的有效控制

提出小波函数反馈控制法,分别实现了在四种不同的初始质子分布情形下对强流质子束的束晕混沌的有效控制.控制后束晕强度因子变为零,束均方根半径、束横向动量平方和的平均值和相对平均发射度比控制前都减少至1/2—1/3.结果表明该方法十分有效,具有应用前景 关键词： 小波函数反馈法 束晕混沌 强流质子束     

激光加速质子束空间电荷力研究

激光加速器可以输出具有独特品质的质子束,例如μm尺寸、ps脉冲长度和高峰值电流。强流粒子束的空间电荷力效应较强,对面向应用的束流传输提出了挑战。通过二维PIC模拟研究了激光加速后与质子速度接近的电子的影响。采用椭球模型估算空间电荷力的影响,比较不同电荷分布的差异。结果表明每束团质子数超过1010后空间电荷力显著影响质子束传输,甚至严重破坏束流品质。空间电荷力的影响在20 ps后显著减弱,离开靶约1.2 mm。     

激光加速质子束空间电荷力研究（英文）

激光加速器可以输出具有独特品质的质子束,例如μm尺寸、ps脉冲长度和高峰值电流。强流粒子束的空间电荷力效应较强,对面向应用的束流传输提出了挑战。通过二维PIC模拟研究了激光加速后与质子速度接近的电子的影响。采用椭球模型估算空间电荷力的影响,比较不同电荷分布的差异。结果表明每束团质子数超过10¹⁰后空间电荷力显著影响质子束传输,甚至严重破坏束流品质。空间电荷力的影响在20 ps后显著减弱,离开靶约1.2 mm。     

强流加速器中束晕-混沌的延迟反馈控制

简要分析了延迟反馈法运用于束晕混沌控制的理论可行性并实现了5种不同的初始质子分布情形下强流加速器中束晕混沌的有效控制.控制律为线性,反馈量小,有利于技术实现和降低控制代价,可为强流加速器的工程实现提供参考. 关键词： 束晕-混沌 强流加速器 延迟反馈     

低能强流带电粒子束的非线性空间电荷效应理论

本文用解析方法研究低能强流带电粒子束的非线性空间电荷效应。文中确定了粒子温度为零的束的发射度图形形状的变化和束的初始束流密度分布之间的关系,由此导出了计算粒子温度不很高的束在非线性空间电荷场作用下发射度图形变化和有效发射度增长的近似方法。     

散裂靶中质子束窗的散射效应

 质子束窗是在高功率靶区中的一个分界窗,它将质子输运线上高真空区域和氦容器中的氦环境分开。在其他散裂中子源中质子束窗的热效应以及机械问题都已经被研究过了,但质子束在该窗中散射效应的研究却很少被报导,然而在靶设计中如果没有处理好质子束窗的散射效应会有很大的问题。报导了质子束窗散射效应的模拟计算结果,包括不同质子束窗的材料和结构选择,并以中国散裂中子源（CSNS）为例,介绍了在CSNS一期和二期中质子束窗采用周边水冷的铝合金单层结构,CSNS三期采用中间水冷的铝合金夹层结构。文中给出了不同结构的质子束窗和不同的与靶距离散射效应对靶上经非线性磁铁均匀化的束流分布的影响的模拟计算结果。模拟结果显示质子窗的散射效应对束流损失和靶上的束流分布有重要的影响。     

强流束晕-混沌的外部磁场自适应控制

 研究了强流质子束在周期聚焦磁场通道中束晕 混沌的外部磁场自适应控制方法,给出了磁场控制方程。将该方法应用在多粒子模型中,实现了对4种不同初始分布质子束的束晕 混沌的有效控制,得到了消除束晕及其再生现象的理想结果。在强流加速器系统中,由于外部磁场是可测和可调的物理量,因此该控制方法有利于实验研究,可为强流质子加速器中周期聚焦磁场的设计和实验提供参考。     

束晕-混沌的神经网络自适应控制

 理论分析了强流离子束在周期磁场聚焦通道中传输时产生的束晕 混沌动力学行为,给出了近似反映实际聚焦磁场的余弦函数形式。然后利用神经网络方法对非线性复杂系统控制的优越性,提出前馈反传神经网络方法对强流离子束中束晕 混沌进行自适应控制。通过适当选择的神经网络控制结构和线性反馈系数以及自适应调整神经网络的权系数,可将强流离子束的包络半径达到束匹配半径的控制目标,且束包络的抖动大小明显减少,束晕 混沌现象得到了明显的抑制。     

Stability Analysis of Some Nonlinear Feedback Control Methods for Beam Halo-Chaos Suppression

Control of beam halo-chaos has been a very challenging subject for research in recent years, in which some nonlinear feedback methods have been developed for suppression of beam halo-chaos in high-current proton linear accelerators. However, stability analysis of such successful nonlinear feedback control methods has not yet been rigorously carried out, which remains an important open topic in the field. In this letter, we present a rigorous mathematical analysis of several nonlinear feedback control methods that are applied to control beam halo-chaos with great success on simulations.     

Nonlinear Control of Beam Halo-Chaos in Accelerator-Driven Clean Nuclear Power System

Beam halo-chaos in high-current accelerators has become a key concerned issue because it can cause excessive radioactivity from the accelerators therefore significantly limits their applications in industry, medicine, and national defense. Some general engineering methods for chaos control have been developed in recent years, but they generally are unsuccessful for beam halo-chaos suppression due to many technical constraints. Beam halo-chaos is essentially a spatiotemporal chaotic motion within a high power proton accelerator. In this paper, some efficient nonlinear control methods, including wavelet function feedback control as a special nonlinear control method, are proposed for controlling beam halo-chaos under five kinds of the initial proton beam distributions (i.e., Kapchinsky-Vladimirsky, full Gauss,3-sigma Gauss, water-bag, and parabola distributions) respectively. Particles-in-cell simulations show that after control of beam halo-chaos, the beam halo strength factor is reduced to zero, and other statistical physical quantities of beam halo-chaos are doubly reduced. The methods we developed is very effective for suppression of proton beam halo-chaos in a periodic focusing channel of accelerator. Some potential application of the beam halo-chaos control in experiments is finally pointed out.     

Control of Beam Halo-Chaos Based on Self-Field-Intensity of Particle Beam

The KV beam through an axisymmetric periodic-focusing magnetic field is studied using the particle-core model. A new variable of the self-field-intensity of particle beam is selected, and an idea of self-field feedback controller is proposed based on the variable for controlling the halo-chaos. We perform multiparticle simulation to control the halo by using the self-field feedback controller. The numerical results show that the halo-chaos and its regeneration can be eliminated effectively, and that the density uniformity can be found at the centre of beam as long as an appropriate control method is chosen. The control method may be operated in the experiment, because field intensity measurement is easy.     

Controlling Beam Halo-Chaos via Time-Delayed Feedback

The study of controlling high-current proton beam halo-chaos has become a key concerned issue for many important applications. In this paper, time-delayed feedback control method is proposed for beam halo-chaos. Particle in cell simulation results show that the method is very effective and has some advantages for high-current beam experiments and engineering.     

强流加速器中束晕-混沌的小波间隔反馈控制

在束晕-混沌的小波函数控制已实现的基础上,给出了一种形式更为简单的小波函数控制器,并研究了束晕混沌的多周期间隔反馈控制方法.以控制初始条件遵从Kapchinshij-Vladimirskij分布的离子束为例进行模拟,结果表明,通过适当选择间隔的周期数和小波控制器的控制参数,仍能很有效地对束晕混沌进行控制,并能达到消除束晕及其再生现象的理想结果.研究结果可望为实用强流加速器的研制提供有价值的参考 关键词： 小波函数控制器 多周期间隔 束晕-混沌 强流离子束     

Control of Halo-Chaos in Beam Transport Network via Neural Network Adaptation with Time-Delayed Feedback

Subject of the halo-chaos control in beam transport networks (channels) has become a key concerned issue for many important applications of high-current proton beam since 1990'. In this paper, the magnetic field adaptive control based on the neural network with time-delayed feedback is proposed for suppressing beam halo-chaos in the beam transport network with periodic focusing channels. The envelope radius of high-current proton beam is controlled to reach the matched beam radius by suitably selecting the control structure and parameter of the neural network, adjusting the delayed-time and control coefficient of the neural network.     

Control of beam halo-chaos by Gauss function in the triangle periodic-focusing channel

This paper studies the Kapchinsky-Vladimirsky （K-V） beam through a triangle periodic-focusing magnetic field by using the particle-core model. The beam halo-chaos is found, and an idea of Gauss function controller is proposed based on the strategy of controlling the halo-chaos. It performs multiparticle simulation to control the halo by using the Gauss function control method. The numerical results show that the halo-chaos and its regeneration can be eliminated effectively, and that the radial particle density is uniform at the centre of the beam as long as the control method and appropriate parameter are chosen.     

周期聚焦磁场中束晕-混沌的实Morlet小波函数控制

 基于束晕-混沌的非线性控制策略,对周期性聚焦磁场中初始分布满足K-V分布的粒子束进行模拟研究,提出了控制其束晕-混沌的实Morlet小波函数控制器,并给出具体的实施方案。数值模拟研究表明,在适当的参数条件下,运用这种方法不仅可以消除束晕及其再生现象,达到对束晕-混沌的有效控制,而且可以控制束流到均匀分布。     

Controlling Beam Halo-Chaos by Adaptive Control Exterior Magnetic Field

In this paper, the parametric adaptive method for controlling the beam halo-chaos in the periodic focusing channels of high-current proton linacs is presented. The study of proton beam halo-chaos based on controlled beam envelope equation and the results of particles-in-cell simulations for macro-particle beam show that the proton beam chaotic envelope as well as the beam rsm radius can be controlled to the beam matched radius using this method.For the Kapchinskij-Vladimirskij (K- V) distribution of initial proton beam, all statistical physical, quantities of the beam halo-chaos are largely reduced. This control method has an advantage of the control halo-chaos since the exterior magnetic field as controlled parameter can be rather easily adjusted in the periodical magnetic focusing channels for the experiment.