Thermal Management Enables Bright and Stable Perovskite Light-Emitting Diodes

The performance of lead-halide perovskite light-emitting diodes (LEDs) has increased rapidly in recent years. However, most reports feature devices operated at relatively small current densities (<500 mA cm⁻²) with moderate radiance (<400 W sr⁻¹ m⁻²). Here, Joule heating and inefficient thermal dissipation are shown to be major obstacles toward high radiance and long lifetime. Several thermal management strategies are proposed in this work, such as doping charge-transport layers, optimizing device geometry, and attaching heat spreaders and sinks. Combining these strategies, high-performance perovskite LEDs are demonstrated with maximum radiance of 2555 W sr⁻¹ m⁻², peak external quantum efficiency (EQE) of 17%, considerably reduced EQE roll-off (EQE > 10% to current densities as high as 2000 mA cm⁻²), and tenfold increase in operational lifetime (when driven at 100 mA cm⁻²). Furthermore, with proper thermal management, a maximum current density of 2.5 kA cm⁻² and an EQE of ≈1% at 1 kA cm⁻² are shown using electrical pulses, which represents an important milestone toward electrically driven perovskite lasers.     

干湿联合冷却塔冷却节水分析软件开发及应用

为实现对干湿联合冷却塔冷却特性、节水特性的综合分析，编制干湿联合冷却塔校核计算流程，基于Visual Studio开发平台，本文开发了干湿联合冷却塔冷却节水特性分析优化软件。通过对某在运干湿联合冷却塔进行冷却节水特性计算，验证了所开发软件计算结果的准确性；在消雾节水计算结果基础上，对标干湿联合消雾冷却塔验收测试规程，生成其成雾频率曲线、耗水量曲线、塔雾指数、冷却特性曲线，综合分析其消雾特性、节水特性及冷却特性，从而确定了干湿联合冷却塔的最佳运行工况。同时运用所开发软件对比分析了某冷却塔设计干段散热面积对其消雾特性、节水特性及冷却特性的耦合影响，并分析了百叶窗开度对干湿联合冷却塔性能的影响，为干湿联合冷却塔的运行优化和设计优化提供了工具性软件支持。     

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.     

轧机垂直系统动力学参数辨识

 针对轧机垂直系统动力学参数可信度不足等问题，提出一种基于实测数据的改进粒子群算法辨识轧机垂直系统动力学参数的方法。首先,将轧机垂直系统刚度和阻尼考虑成达芬振子和范德波尔振子，构建轧机垂直系统非线性动力学模型，并对粒子群算法进行改进；然后，通过数值仿真算例辨识得到系统在感染噪声和不含噪声时的动力学参数，验证了该算法的有效性；最后，以现场某轧机垂直系统为研究对象，基于现场实测数据，应用该算法进行辨识，得到了轧机垂直系统动力学参数估计，通过实测位移、速度和加速度信号分别与辨识后的位移、速度和加速度信号进行对比，证明该方法辨识轧机垂直系统动力学参数结果可靠，具有一定的工程应用价值。     

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。     

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.