Thermodynamic analysis and parametric study of an intercooled–reheat closed-cycle gas turbine on the basis of a new isentropic exponent

The thermodynamic analysis and parametric study of an intercooled–reheat closed-cycle gas turbine is presented in this paper, on the basis of a new (harmonic mean) isentropic exponent. An analytical expression is derived for the optimum pressure ratio and maximum non-dimensional net work output. It is found that the optimum pressure ratio and the maximum non-dimensional net work are high when the ratio of extreme temperatures of cycle (i.e. T _max and T _min) and isentropic efficiencies of compressor and turbine (i.e. η_c and η_t) are high. The theoretical results are also compared with the practical conditions of power plant.     

Prediction of Core Losses of Three-Phase Distribution Transformer

Transformers are normally designed and built for use at rated frequency and sinusoidal load current. A non-linear load on a transformer leads to harmonic power losses which cause increased operational costs and additional heating in transformer parts. It leads to higher losses, early fatigue of insulation, premature failure and reduction of the useful life of the transformer. To prevent these problems, the rated capacity of transformer which supplies harmonic loads must be reduced. In this work, a typical 50 kVA three-phase distribution transformer with real practical parameters is taken under non-linear loads generated due to domestic loads. The core losses is evaluated using the three dimensional model of the transformer developed in FEM （finite element method） program based on valid model of transformer under high harmonic conditions. And finally a relation associated with core losses and amplitude of high harmonic order are reviewed ＆ analyzed and then a comparison is being carried out on the results obtained by different excitation current in transformer windings.     

Incorporating risk measures in closed-loop supply chain network design

This paper considers a location-allocation problem in a closed-loop supply chain (CLSC) with two extensions: first, demand and prices of new and return products are regarded as non-deterministic parameters and second, the objective function is developed from expected profit to three types of mean-risk ones. Indeed, design and planning an integrated CLSC in real-world volatile markets is an important and necessary issue. Further, risk-neutral approaches, which are considered expected values, are not efficient for such uncertain conditions. Hence, this paper, copes with the design and planning problem of a CLSC in a two-stage stochastic structure. Besides, risk criteria are considered through using three types of popular and well-behaved risk measures: mean absolute deviation, value at risk and conditional value at risk (CVaR). Consequently, three types of mean-risk models are developed as objective functions and decision-making procedures are undertaken based on the expected values and risk adversity criteria. Finally, performances of the developed mean-risk models are evaluated in various aspects. Results reveal that the inefficiencies of risk-neutral approaches can be overcome. In addition, in terms of quality of solutions, the acceptability of CVaR is proved when it is compared to other risk measures.     

Meta-heuristics for the distributed two-stage assembly scheduling problem with bi-criteria of makespan and mean completion time

This paper focuses on the distributed two-stage assembly flowshop scheduling problem for minimising a weighted sum of makespan and mean completion time. This problem involves two inter-dependent decision sub-problems: (1) how to allocate jobs among factories and (2) how to schedule the assigned jobs at each factory. A mathematical model is formulated for solving the small-sized instances of the problem. Since the NP-hardness of the problem, we also proposed a variable neighbourhood search (VNS) algorithm and a hybrid genetic algorithm combined with reduced variable neighbourhood search (GA-RVNS) to solve the distributed two-stage assembly flowshop scheduling problems and approximately optimise makespan and mean completion time simultaneously. Computational experiments have been conducted to compare the performances of the model and proposed algorithms. For a set of small-sized instances, both the model and the proposed algorithms are effective. The proposed algorithms are further evaluated on a set of large-sized instances. The results statistically show that both GA-RVNS and VNS obtain much better performances than the GA without RVNS-based local search step (GA-NOV). For the instances with small numbers of jobs, VNS achieves better performances than GA-RVNS. However, for the instances with large numbers of jobs, GA-RVNS yields better performances than the VNS. It is also shown that the overall performances of VNS are very close to GA-RVNS with different numbers of factories, weights given to makespan and numbers of machines at the first stage.     

Prediction of thermal conductivities of laminated composites using penny-shaped fillers

A new model is proposed to predict the thermal conductivities of laminated composites, where the Eshelby method modified with Mori-Tanaka’s mean field approach is employed to consider the interaction effect. Based on the equivalency of composites with penny-shaped fillers and composites with layers of components, each lamina is considered as a penny-shaped filler and its thermal conductivities are computed by modified Eshelby method. The laminated composites are then simulated as the matrix and penny-shaped fillers of different thermal conductivities. By comparing the results of the laminated composites predicted by the present model and conventional approach combined with the potential theory and electrical analogy, the applicability of the present model to predict the thermal conductivities of the laminated composites is validated. This paper was recommended for publication in revised form by Associate Editor Dongsik Kim Jae-Kon Lee received a B.S. degree in Mechanical Engineering from Seoul National University in 1985. He then went on to receive his M.S. degree from KAIST and Ph.D. degrees from University of Washington in 1987 and 1996, respectively. Dr. Lee is currently a Professor at the School of Mechanical and Automotive Engineering at Catholic University of Daegu in Kyeongsan, Korea. Dr. Lee’s research interests are in the area of design and analysis of smart composite materials using mechanical, thermal, and piezoelectric properties.     

LMD时频分析方法的端点效应在旋转机械故障诊断中的影响

为评估局域均值分解(LMD)受端点效应影响的程度,提出了一种基于能量的端点效应评价指标,并将LMD的端点效应与经验模态分解(EMD)的端点效应进行了比较。因包络线的定义方法不同,LMD在端点附近未定义的包络线较短,端点效应的程度也较轻。提出的端点效应镜像延拓抑制方法经仿真证明效果良好。将LMD应用于提取转子裂纹的故障特征,可获得满意的实验结果。     

双环平行网络时延及可靠性分析

针对环网的不足,提出双环平行网络,并分析双环平行网络的时延和可靠性。使用图论知识表示双环平行网络的拓扑结构,在此基础上分析其直径、平均距离、连通度和容错性等性能参数。双环平行网络的直径和平均距离约为环网的一半,其传输时延也约为环网的一半。双环平行网络的连通度和边连通度比环网大1,其可靠性远远高于环网。实验结果表明,环网与双环平行网络的时延之比为1.90∶1,验证了双环平行网络的传输时延约为环网一半的结论。     

水煮中心温度对鸡胸肉食用品质的影响

以鸡胸肉为原料,研究水煮中心温度对鸡胸肉感官品质、蒸煮损失、剪切力、肉色等食用指标的影响,为鸡肉在加工时选择合适的煮制温度提供参考。结果表明:水煮中心温度为90℃时,鸡胸肉的感官品质最佳;在70～90℃时蒸煮损失显著增加,持水性下降速率较快;80℃是鸡胸肉剪切力值改变的关键温度点;70,90℃是鸡胸肉肉色改变的关键温度点。     

马兰黄土压实工艺的试验研究

针对马兰黄土的压实工艺开展了击实试验及系列现场试验研究,分析含水量对压实效果的影响和单项工艺及新型组合工艺的压实工效,给出压实马兰黄土主要物理力学性质、填筑地基承载力特征值及土体变形模量的参考值。试验结果表明:马兰黄土水敏感性强,含水量控制是其压实效果的关键因素,现场压实施工的土体含水量控制范围可取12%～14%,最大干密度可取1.85～1.89 g/cm3,压实施工可首选振碾强夯组合压实工艺,该工艺施工速度快,场地适应性好,可较好地应用于沟壑填筑施工。     

对“地下水化学影响的岩土工程勘察评价”商榷的回复

结合商榷意见,依据《地下水化学影响的岩土工程勘察评价》一文讨论内容,就地下水样本数量、化学性质的统计分析及标准值推断问题进行了答复和讨论。