Shape optimization of bi-directional flow passage components based on a genetic algorithm and computational fluid dynamics

The inlet/outlet is an important part of a water conveyance system in a pumped storage power station (PSPS). Its hydraulic characteristics are directly related to the operation and economic benefit of the PSPS. Frequent changes between inflow and outflow operations pose significant challenges in the design of the inlet/outlet diffusion segment shape. In this study, an effective optimization method, including three-dimensional parametric modelling, computational fluid dynamics and a genetic algorithm, is introduced and coupled to the design of the diffusion segment shape. The hydraulic characteristics of bi-directional flow, including the head loss, velocity uneven distribution and uneven discharge distribution, are selected as the objective function in the optimization method. Using this method, the recommended shape of the inlet/outlet is studied and its hydraulic characteristics are discussed. The results indicate that the optimized inlet/outlet has better performance.     

基于大数据分析的分布式MOLAP技术研究

在计算机系统运行以及研究环节中,会存在大量的规模效应,此类状况难以避免,要想有效解决此类问题,就需要利用分布式的处理方式,开展对文件系统的分析。文章对分布式多维联机分析过程(MOLAP)的数据模型进行了分析,从维编码的算法、映射归约(MapReduce)算法的实现、分析维的遍历算法等方面作深入探讨。     

一种下肢运动意图识别算法性能实时测评系统* .txt

摘要：对腿部运动意图识别算法的实时性能进行综合可靠的评价是实现下肢假肢灵活稳定控制的前提。提出一种逐层分级的基于下肢运动意图识别算法的实时测评方法，对算法的可靠性、稳定性以及运动意图识别速度进行综合评价。利用开发的运动意图识别算法评测系统，对基于肌电信号源和机械信号源的两种运动意图识别算法进行了实时性能测试，发现肌电信号源的算法识别时间大于机械信号源算法，但是其算法稳定性优于机械信号源算法。进一步地，还利用该评测系统有效地区分出正常识别策略与异常识别策略，发现正常策略的动作识别稳定系数比异常策略高25%左右。因此，所提的基于下肢运动意图识别算法的实时测评方法，能够对不同信号源算法以及不同识别策略的实时性能进行有效评价，为智能下肢假肢控制系统开发提供可供参考的测试平台。 .txt     

Optimal design of Raman fibre amplifier based on terminal value optimization strategy and shuffled frog leaping algorithm

This paper introduces an evolutionary algorithm, Shuffled Frog Leaping Algorithm (SFLA), to solve the optimization problem in designing the multi-pumped Raman Fibre Amplifier (RFA). SFLA is a powerful optimizer tool because of its efficient mathematical expressions and global search capability. We utilize SFLA to determine the optimal pump wavelengths and pump powers by minimizing the gain ripple of RFA. To accelerate calculations, a terminal value optimization strategy (TVOS) is incorporated into the evolution of SFLA. This proposed strategy takes the terminal power values of pumps as the decision variables in optimization. Then, the optimal original power values of the pumps are obtained by solving the Power Coupled Equations once, without using the traditional method of repetitive guesses.The combination of SFLA and TVOS enhances the efficiency of optimization and accelerates calculation, while satisfying the design requirements of RFA.The simulation results show that nearly 65% of computational time has been saved compared with the traditional average power analysis. The 4-pumped C+L band of backward multi-pumped RFA with the average net gain of 0 dB, 1 dB and 2 dB are designed individually, where the gain ripple is less than 0.64 dB. The combination of SFLA and TVOS enhance the optimization efficiency and improve the performance of RFA with good gain profile.     

New empirical correlation for estimation of vaporization enthalpy of algerian saharan blend petroleum fractions

A Real-coded Genetic Algorithm has been used to develop a new correlation to estimate the enthalpy of vaporization for pure compounds and petroleum fractions as a function of the normal boiling point and specific gravity. In developing the correlation 80% of the data was used and the remaining are used for validation. The results of the proposed correlations are compared to others in literature. The comparison indicates that the proposed model is simple to use and more accurate than the most common correlations for predicting the enthalpy of vaporization of pure compounds and petroleum fractions.     

宇宙线缪子散射成像模拟与算法研究

本文验证了基于Micromegas探测器的宇宙线缪子散射成像系统进行快速核材料检测的可行性，并对实验室宇宙线缪子成像系统原型进行参数估算。基于Geant4程序开发了用于模拟宇宙线缪子物理过程、传输径迹及Micromegas探测器响应的模拟程序。在模拟数据的基础上，实现并改进了两种主要的宇宙线缪子散射成像算法。根据模拟和成像结果，1 m×1 m成像系统可在10 min内检测到被重元素屏蔽的核材料。10 cm×10 cm成像系统的缪子事例触发率为0.16 s^-1，要获得较为清晰的成像结果，要求探测器位置分辨率达到300 μm，探测器增益为1 000时实际测量事例至少需要20 h。     

An intelligent EGWO-SCA-CS algorithm for PSS parameter tuning under system uncertainties

This paper proposes a novel hybrid technique called enhanced grey wolf optimization-sine cosine algorithm-cuckoo search (EGWO-SCA-CS) algorithm to improve the electrical power system stability. The proposed method comprises of a popular grey wolf optimization (GWO) in an enhanced and hybrid form. It embraces the well-balanced exploration and exploitation using the cuckoo search (CS) algorithm and enhanced search capability through the sine cosine algorithm (SCA) to elude the stuck to the local optima. The proposed technique is validated with the 23 benchmark functions and compared with state-of-the-art methods. The benchmark functions consist of unimodal, multimodal function from which the best suitability of the proposed technique can be identified. The robustness analysis also presented with the proposed method through boxplot, and a detailed statistical analysis is performed for a set of 30 individual runs. From the inferences gathered from the benchmark functions, the proposed technique is applied to the stability problem of a power system, which is heavily stressed with the nonlinear variation of the load and thereby operating conditions. The dynamics of power system components have been considered for the mathematical model of a multimachine system, and multiobjective function has been framed in tuning the optimal controller parameters. The effectiveness of the proposed algorithm has been assessed by considering two case studies, namely, (i) the optimal controller parameter tuning, and (ii) the coordination of oscillation damping devices in the power system stability enhancement. In the first case study, the power system stabilizer (PSS) is considered as a controller, and a self-clearing three-phase fault is considered as the system uncertainty. In contrast, static synchronous compensator (STATCOM) and PSS are considered as controllers to be coordinated, and perturbation in the system states as uncertainty in the second case study.     

基于目标级联技术的含风电互联电网机组组合策略

针对含风电互联电网日前安全约束机组组合的规模大、约束复杂、求解困难等问题,提出基于目标级联分析技术的分散协调优化策略。将问题分解为负责区域间边界节点电压相角协调的上层优化问题和以并行方式独立优化各区域发电计划的下层优化问题。下层优化以弃风电量期望和电量不足期望,量化各区域内风电、负荷预测误差,以及常规机组强迫停运等系统运行不确定性所带来的风险,并以罚函数的形式引入目标函数,以综合优化系统可靠性与经济性。2区域12节点系统和IEEE RTS96三区域互联系统算例仿真验证所建模型和算法的有效性。     

楼宇型分布式能源系统设备容量和运行策略优化研究

设备容量优化和运行策略优化是分布式能源系统设计，运行的关键问题。为实现分布式能源系统的经济效益，能效水平和环境效益最大化，针对楼宇型分布式能源系统建立了相对普适化的物理模型和数学模型，以粒子群优化算法和线性规划相结合，采用两阶段优化方法计算系统的最优容量配置，并给出运行策略。以某写字楼的分布式能源系统为例，得到最优的系统设备容量和全年逐时运行策略，并采用遍历法验证计算结果的准确性。优化的分布式能源系统与传统供能系统相比，费用年值降低7.79%，年总能耗降低24.18%，污染物排放量减少了62.77 %。     

Chemical process fault diagnosis based on enchanted machine‐learning approach

In the chemical industry, fault diagnosis is a challenging task due to the complexity of chemical equipment. This paper proposes a machine learning‐based approach to achieve the goal of fault diagnosis. First, in order to reduce the impact of redundant features, support vector machine recursive feature elimination (SVMRFE) is used to select important features. The trained probabilistic neural network (PNN) is then used for fault diagnosis. Considering that the diagnostic performance is affected by its hidden layer element smoothing factor (σ), the modified bat algorithm (MBA) is used to optimize the PNN to obtain optimal global parameter values. The MBA adopts a better optimization mechanism than the basic algorithm and achieves excellent global convergence. It can globally optimize the smoothing factor, which effectively improves the fault diagnosis ability of the PNN. During the testing of the Tennessee Eastman (TE) process data set, we evaluate the performance of the proposed model by comparing the F₁‐score and accuracy of the different methods. The charts provided describe the fault diagnostic results and classification for the different models. The results indicate that the MBA has a better optimization ability than other traditional optimization algorithms. At the same time, the combination method proposed in this paper is also superior to others and can significantly improve the accuracy of TE process fault diagnosis.