γ辐照加工用新型工作模体设计研究

本文研究设计了一种用于获取γ辐照装置辐射场和货物剂量场真实分布的新型工作模体。基于真实γ辐照装置参数构建了有效可用的模拟辐射场，提出了新型工作模体的结构和填料设计方法。采用蒙特卡罗方法和随机填充方法（RCS）模拟计算剂量计套管材料与壁厚、填料小球尺寸、空心填料小球尺寸与壁厚、小球填充方式等影响模体剂量学性能的主要因素的分布规律。在满足计算置信度的前提下，参数优化取值范围为：套管采用壁厚为3~5 mm的铝管，对辐射场干扰不超过4.372 23%；填料选择外径为1~4 cm、壁厚为1.1~11.5 mm、材料等效性好、货物密度模拟范围为0.1~0.5 g/cm³的聚丙烯小球，对辐射场干扰不超过9.998 44%；均匀填充和随机填充模式对辐射场干扰基本持平，且均不超过10%。结果表明，当前设计可行有效，投入低、兼顾参数多且量程更宽，适合推广应用。     

A novel minimum weight formulation of topology optimization implemented with reanalysis approach

In this paper, we develop an efficient diagonal quadratic optimization formulation for minimum weight design problem subject to multiple constraints. A high-efficiency computational approach of topology optimization is implemented within the framework of approximate reanalysis. The key point of the formulation is the introduction of the reciprocal-type variables. The topology optimization seeking for minimum weight can be transformed as a sequence of quadratic program with separable and strictly positive definite Hessian matrix, thus can be solved by a sequential quadratic programming approach. A modified sensitivity filtering scheme is suggested to remove undesirable checkerboard patterns and mesh dependence. Several typical examples are provided to validate the presented approach. It is observed that the optimized structure can achieve lighter weight than those from the established method by the demonstrative numerical test. Considerable computational savings can be achieved without loss of accuracy of the final design for 3D structure. Moreover, the effects of multiple constraints and upper bound of the allowable compliance upon the optimized designs are investigated by numerical examples.     

基于(火用)效率目标的环冷机余热回收系统操作参数优化

摘要：针对烧结环冷机余热回收利用率不高的难题，采用分析法建立了评价某钢铁厂烧结环冷机余热回收系统运行效率的效率模型。基于多孔介质模型、局部非热平衡方程、真实气体SRK方程建立环冷机内气固两相换热模型。通过CFD仿真模拟，探究料层高度、循环风机输入烟气温度、烧结矿底部入口风速三项可控环冷机运行工艺参数对系统效率的影响规律。结果表明，料层厚度在1～1.5 m区间每增加0.1 m，效率增加0.8%～1.1%；循环风温在100～140℃之间每增加10℃，效率增加1.4%～1.5%；烧结矿底部入口风速在0.9～1.9 m/s之间每增加0.1 m/s，效率降低0.18%～0.24%。在此基础上，基于工业运行数据建立效率正交试验优化模型，提高了该余热回收系统3.42%的效率。     

论三峡水库“蓄清排浑”运用方式及其优化

泥沙问题是三峡工程的关键技术问题之一,在三峡工程论证和初步设计阶段提出水库采取"蓄清排浑"的运用方式,可以解决泥沙问题。2003年水库蓄水运用以来的实践表明,水库基本遵循了"蓄清排浑"调度运用原则,并根据上游来水来沙减少等新情况对水库运用方式进行了优化调整。本文系统分析了三峡水库"蓄清排浑"运行方式及其优化调整的利弊,包括提前5年实施175 m试验性蓄水、汛期水位动态变化、汛末提前蓄水等对水库淤积和坝下游河道演变的影响,提出了进一步优化水库调度方式,形成"蓄清排浑"运用的新模式,保持水库长期使用的建议,试图为三峡水库科学高效安全运用提供科技支撑。     

A new linearly constrained minimum variance beamformer for reconstructing EEG sparse sources

Brain source imaging based on EEG aims to reconstruct the neural activities producing the scalp potentials. This includes solving the forward and inverse problems. The aim of the inverse problem is to estimate the activity of the brain sources based on the measured data and leadfield matrix computed in the forward step. Spatial filtering, also known as beamforming, is an inverse method that reconstructs the time course of the source at a particular location by weighting and linearly combining the sensor data. In this paper, we considered a temporal assumption related to the time course of the source, namely sparsity, in the Linearly Constrained Minimum Variance (LCMV) beamformer. This assumption sounds reasonable since not all brain sources are active all the time such as epileptic spikes and also some experimental protocols such as electrical stimulations of a peripheral nerve can be sparse in time. Developing the sparse beamformer is done by incorporating L1-norm regularization of the beamformer output in the relevant cost function while obtaining the filter weights. We called this new beamformer SParse LCMV (SP-LCMV). We compared the performance of the SP-LCMV with that of LCMV for both superficial and deep sources with different amplitudes using synthetic EEG signals. Also, we compared them in localization and reconstruction of sources underlying electric median nerve stimulation. Results show that the proposed sparse beamformer can enhance reconstruction of sparse sources especially in the case of sources with high amplitude spikes.     

基于协同优化算法的流速仪检定系统设计

提出了一种小型轻便的流速仪检定系统的设计方案,并运用改进的多学科协同优化方法求解各学科设计变量的最优解。首先介绍了算法思想及改进措施,并根据系统设计要求建立了各学科的设计变量、目标函数和约束条件；其次,运用遗传算法求解各学科设计变量的最优解,并根据优化结果完善了系统的设计方案,同时运用计算机仿真等方法验证了优化结果的可行性。结果表明,优化后的检定系统满足流体力学效应、匀速运动时间、系统重量等设计要求,同时证明了协同优化算法解决多学科设计优化问题的有效性。     

A hierarchical simple particle swarm optimization with mean dimensional information

To reduce the negative influence of the overemphasis of gbest the dimensional information of particle is introduced to be a new example. This additional information source is incorporated into simple PSO to establish a simpler position model. Another two simpler position updating models, cognition only model and social only model, based on the simple PSO algorithm are presented as well. Time hierarchy strategy is extended from probability hierarchy, both aiming to make full use of advantages of three models. Three models are used with time or probability hierarchy to update each particle’s position. Thus, two proposed algorithms THSPSO and PHSPSO are finally obtained. Experiments are conducted on fifteen benchmark functions. The results demonstrate the two proposed algorithms both have excellent performances for basic functions compared with other popular PSO variants. Probability hierarchy strategy is more effective than time hierarchy strategy in general.     

粒子群属性聚类的位置隐私保护

针对基于位置服务中连续查询情况下，用户自身属性信息很容易被攻击者获取，并通过关联获得用户位置隐私的情况，提出了一种利用粒子群聚类加速相似属性用户寻找，并由相似属性匿名实现用户位置泛化的隐私保护方法。该方法利用位置隐私保护中常用的可信中心服务器，通过对发送到中心服务器中的查询信息进行粒子群属性聚类，在聚类的过程中加速相似属性用户的寻找过程，由相似属性用户完成位置泛化，以此实现位置隐私保护。实验结果证明，这种基于粒子群属性聚类的隐私保护方法具有高于同类算法的隐私保护能力，以及更快的计算处理速度。     

A flexible air separation process: 1. Design and steady-state optimizations

The flexible operation of energy-intensive processes, such as cryogenic air separation, has economic potential due to increasing fluctuations of the electricity markets. Multiproduct air separation processes with high ratios of liquid product are very promising for flexible operation due to storable products. We present a process design with an integrated liquefication cycle and liquid assist operation, that facilitates a high liquid product ratio and a flexible process operation. We use a mechanistic dynamic process model in steady-state process optimizations covering the wide operational range of the proposed process. The optimization results show that the power demand can be varied in a range from 3.5 to 28 MW without violating operational constraints by changing the nitrogen and oxygen production rates. Thus, the proposed process is a promising air separation candidate for flexible operation with respect to fluctuating electricity markets.     

An engineering method for complex structural optimization involving both size and topology design variables

This work presents an engineering method for optimizing structures made of bars, beams, plates, or a combination of those components. Corresponding problems involve both continuous (size) and discrete (topology) variables. Using a branched multipoint approximate function, which involves such mixed variables, a series of sequential approximate problems are constructed to make the primal problem explicit. To solve the approximate problems, genetic algorithm (GA) is utilized to optimize discrete variables, and when calculating individual fitness values in GA, a second-level approximate problem only involving retained continuous variables is built to optimize continuous variables. The solution to the second-level approximate problem can be easily obtained with dual methods. Structural analyses are only needed before improving the branched approximate functions in the iteration cycles. The method aims at optimal design of discrete structures consisting of bars, beams, plates, or other components. Numerical examples are given to illustrate its effectiveness, including frame topology optimization, layout optimization of stiffeners modeled with beams or shells, concurrent layout optimization of beam and shell components, and an application in a microsatellite structure. Optimization results show that the number of structural analyses is dramatically decreased when compared with pure GA while even comparable to pure sizing optimization.