Exactly satisfying initial conditions neural network models for numerical treatment of first Painlevé equation

In this paper, novel computing approach using three different models of feed-forward artificial neural networks (ANNs) are presented for the solution of initial value problem (IVP) based on first Painlevé equation. These mathematical models of ANNs are developed in an unsupervised manner with capability to satisfy the initial conditions exactly using log-sigmoid, radial basis and tan-sigmoid transfer functions in hidden layers to approximate the solution of the problem. The training of design parameters in each model is performed with sequential quadratic programming technique. The accuracy, convergence and effectiveness of the proposed schemes are evaluated on the basis of the results of statistical analyses through sufficient large number of independent runs with different number of neurons in each model as well. The comparisons of these results of proposed schemes with standard numerical and analytical solutions validate the correctness of the design models.     

Mathematical representation of radiality constraint in distribution system reconfiguration problem

Distribution systems are most commonly operated in a radial configuration for a number of reasons. In order to impose radiality constraint in the optimal network reconfiguration problem, an efficient algorithm is introduced in this paper based on graph theory. The paper shows that the normally followed methods of imposing radiality constraint within a mixed-integer programming formulation of the reconfiguration problem may not be sufficient. The minimum-loss network reconfiguration problem is formulated using different ways to impose radiality constraint. It is shown, through simulations, that the formulated problem using the proposed method for representing radiality constraint can be solved more efficiently, as opposed to the previously proposed formulations. This results in up to 30% reduction in CPU time for the test systems used in this study.     

Fundamental Evaluation of Power Supply and Rectifiers for Wireless Power Transfer Using Magnetic Resonant Coupling

This paper provides a fundamental analysis of a power supply and rectifiers for wireless power transfer using magnetic resonant coupling (MRC). MRC enables efficient wireless power transfer over middle‐range transfer distances. MRC for wireless power transfer should operate at a high frequency in the industry science medical band, such as 13.56 MHz, because the size of the transfer device decreases at higher transfer frequencies. Therefore, the output frequency of the power supply on the transmitting side should be 13.56 MHz. In addition, the rectifier on the receiving side is operated at a high frequency. This paper focuses on the reflected power in the power supply and rectifiers. Thus, the parametric design method is clarified for the power supply, including a low‐pass filter to match the output, the impedance of the power supply with the characteristic impedance of the transmission line. In addition, the effects on the rectifiers of silicon carbide and gallium nitride diodes are confirmed by performing an experiment and a loss analysis.     

高温氢工质热物理性质计算分析

氢工质在新能源与动力、航天推进、化工材料等领域有着广泛应用。通过开展高温氢工质热力学与输运性质研究，建立了原子态氢、分子态氢、热解平衡态氢的热物理性质计算模型，开发了热物性计算程序Prop_H_H2，适用范围为温度100~3 500 K、压力104~5×107 Pa 。验证表明，Prop_H_H2在适用范围内计算氢工质的物性参数合理可靠，在温度200~3 000 K、压力104~107 Pa范围内，程序预测值更加准确，相对偏差在±5%左右。本研究可为氢工质相关的航天推进、应用物理学、能源动力等行业的科研和应用提供支持借鉴。     

Simultaneous synthesis of a heat exchanger network with multiple utilities using utility substages

Heat exchanger network synthesis (HENS) has progressed by using mathematical programming-based simultaneous methodology. Although various considerations such as non-isothermal mixing and bypass streams are applied to consider real world alternatives in modeling phase, many challenges are faced because of its properties within non-convex mixed-integer nonlinear programming (MINLP). We propose a modified superstructure, which contains a utility substage for use in considering multiple utilities in a simultaneous MINLP model. To improve model size and convergence, fixed utility locations according to temperature and series connections between utilities are suggested. The numbers of constraints, discrete, and continuous variables show that overall model size decreases compared with previous research. Thus, it is possible to expand the feasible search area for reaching the nearest global solution. The model's effectiveness and applications are exemplified by several literature problems, where it is used to deduce a network superior to that of any other reported methodology.     

Weighted Superposition Attraction (WSA): A swarm intelligence algorithm for optimization problems – Part 2: Constrained optimization

This paper is the second one of the two papers entitled “Weighted Superposition Attraction (WSA) Algorithm”, which is about the performance evaluation of the WSA algorithm in solving the constrained global optimization problems. For this purpose, the well-known mechanical design optimization problems, design of a tension/compression coil spring, design of a pressure vessel, design of a welded beam and design of a speed reducer, are selected as test problems. Since all these problems were formulated as constrained global optimization problems, WSA algorithm requires a constraint handling method for tackling them. For this purpose we have selected 6 formerly developed constraint handling methods for adapting into WSA algorithm and analyze the effect of the used constraint handling method on the performance of the WSA algorithm. In other words, we have the aim of producing concluding remarks over the performance and robustness of the WSA algorithm through a set of computational study in solving the constrained global optimization problems. Computational study indicates the robustness and the effectiveness of the WSA in terms of obtained results, reached level of convergence and the capability of coping with the problems of premature convergence, trapping in a local optima and stagnation.     

Comparative evaluation of different statistical tools for the prediction of uniaxial compressive strength of rocks

In this study, uniaxial compressive strength (UCS), unit weight (UW), Brazilian tensile strength (BTS), Schmidt hardness (SHH), Shore hardness (SSH), point load index (Is₅₀) and P-wave velocity (V_p) properties were determined. To predict the UCS, simple regression (SRA), multiple regression (MRA), artificial neural network (ANN), adaptive neuro-fuzzy inference system (ANFIS) and genetic expression programming (GEP) have been utilized. The obtained UCS values were compared with the actual UCS values with the help of various graphs. Datasets were modeled using different methods and compared with each other. In the study where the performance indice PI_at was used to determine the best performing method, MRA method is the most successful method with a small difference. It is concluded that the mean PI_at equal to 2.46 for testing dataset suggests the superiority of the MRA, while these values are 2.44, 2.33, and 2.22 for GEP, ANFIS, and ANN techniques, respectively. The results pointed out that the MRA can be used for predicting UCS of rocks with higher capacity in comparison with others. According to the performance index assessment, the weakest model among the nine model is P7, while the most successful models are P2, P9, and P8, respectively.     

黑龙江省节水增粮行动(2012—2015年)实施方案

文章通过对黑龙江省高效节水现状,存在问题的分析,结合黑龙江省高效节水发展的支撑能力,阐述黑龙江省节水增粮目标、任务及总体布局,为黑龙江省2012—2015年节水增粮实施提供依据。     

300M超高强钢在中性盐雾环境中的腐蚀行为及机制

摘要：为了研究300M超高强钢在中性盐雾环境中的腐蚀行为及腐蚀机制，采用失重法，宏观、微观腐蚀形貌分析，三维表面轮廓分析及电化学分析的研究方法，来表征腐蚀实验现象并进行分析。结果表明：300M超高强钢在中性盐雾环境中的腐蚀产物为FeOOH、Fe2O3、Fe(OH)3和Fe3O4；腐蚀速率随着腐蚀时间逐渐降低，腐蚀后期（72h）腐蚀速率降低50%；腐蚀初期以点蚀为主，点蚀坑通过横向扩展，逐渐发展为后期的均匀腐蚀，腐蚀表面形貌呈沟壑状；外腐蚀层对基体的保护能力很弱，Cr元素在锈层靠近基体的一侧偏聚使内腐蚀层具有一定的抗腐蚀性。