Characterization and formation mechanism of nanocrystalline W–Al alloy prepared by mechanical alloying

Tungsten and aluminum elemental powders with composition W–20 wt.% Al were mechanical alloyed in high energy planetary ball mill. Structural and morphological changes of powder particles after different milling times were studied by X-ray diffractometer, scanning electron microscopy and microhardness measurements. Mechanical alloying of this system led to the formation of W–Al alloy as a result of formation of W/Al layered microstructure having faceted interface between layers. This alloy indicated high microhardness value of about 570 Hv.     

中间层成分对GTD-111/IN-718高温合金在瞬时液相连接过程中显微组织和力学性能的影响

研究使用不同的中间层瞬时液相连接两种异种高温合金的适用性.在1100℃、不同时间下瞬时液相连接GTD-111/IN-718体系,研究BNi-2、BNi-3和BNi-9三种类型的中间层对该体系显微组织和力学性能的影响.采用场发射扫描电子显微镜和能量色散光谱技术,研究接头区域的成分变化和显微组织.结果表明,非热凝固区Ni3...     

Age-induced multi-stage transformation in a Ni-rich NiTiHf alloy

Abnormal multi-stage transformations have already been studied in binary Ni-rich NiTi alloys. In this research, this kind of transformation was investigated in a low supersaturated Ni-rich ternary NiTiHf high-temperature shape memory alloy by aging at intermediate temperatures for various durations. Meticulous examinations of the results of differential scanning calorimetry tests demonstrated the heterogeneous precipitation of (Ti,Hf)₃Ni₄ particles and the three-stage transformation (one-stage R and two-stage B19′) in the aged alloy. Aging provided a significant rise in transformation temperatures (TTs) until they reached their equilibrium states, corresponding to the equilibrium Ni content at each aging temperature. Equilibrium TTs were higher when aging was performed at a lower temperature. The remarkable increase in TTs was compared with those in aged Ni-rich NiTi alloys, and discussed based on the variation in valence electron concentration. A model was also proposed for the microstructural evolution during aging. Furthermore, aging provided enhanced hardness and strain recovery for the alloy. In particular, aging at a lower temperature resulted in a considerable improvement in hardness and shape recovery, which was discussed based on the microstructural changes in the aged alloy. Equilibrium Ni content at each aging temperature proved to be a crucial parameter in controlling the alloy properties, even in heterogeneous precipitations.     

The effect of ethane on the performance of commercial polyphenylene oxide and Cardo-type polyimide hollow fiber membranes in CO<Subscript>2</Subscript>/CH<Subscript>4</Subscript> separation applications

Impurities such as hydrogen sulfide, water vapor and heavy hydrocarbons in natural gas have considerable effects on the membrane performance. Small amounts of condensable and polymer soluble components in the feed gas cause swelling or plasticization of glassy membranes, leading to a reduction in membrane selectivity. In the present research the influence of ethane was investigated on the permeance and selectivity of two commercially available hollow fiber membranes, namely Cardo-type polyimide and PPO hollow fibers for CO₂/CH₄ separations. It was concluded that the gas mixture permeation rate was increased in the presence of C₂H₆. However, the CO₂/CH₄ separation factors remained almost the same in the presence and absence of the C₂H₆.     

Effect of optimal spinning reserve requirement on system pollution emission considering reserve supplying demand response in the electricity market

Pollution emission reduction is becoming an inevitable global goal. Incorporating pollution reduction goals into power system operation affects several different aspects, such as unit scheduling and system reliability. At the same time, changes in the energy scheduling change the required optimal reserve amount. Optimal spinning reserve scheduling also affects the energy market scheduling. Optimal reserve allocation changes the energy scheduling, which affect the amount of pollution emission. Therefore, incorporating pollution emission reduction and optimal spinning reserve scheduling cannot be studied separately. Analysis of the system effects of pollution reduction should be performed considering the ancillary service market, specificity the optimal spinning reserve scheduling. This problem is addressed in this paper by incorporating optimal spinning reserve scheduling in a combined environment economic dispatch (CEED) in one objective function. The framework of this paper enables the study of the effect of optimal reserve scheduling and emission reduction as well as an analysis of the system effects of pollution reduction. With the increased AMI and smart grid realization, the reserve supplying demand response (RSDR) is becoming an important player in the reserve market, and thus, these resources are also taken into account. In this paper, the objective function is social cost minimization, including the costs associated with energy provision, reserve procurement, expected interruptions and environmental pollution. A MIP-based optimization method is developed, which reduces the computational burden considerably while maintaining the ability to reach to the optimal solution. The IEEE RTS 1996 is used as a test case for numerical simulations, and the results are presented. The numerical results show that optimal reserve scheduling and RSDR utilization resources have a considerable impact on environmental–economic cost characteristics.     

Multiobjective Calibration of Reservoir Water Quality Modeling Using Multiobjective Particle Swarm Optimization (MOPSO)

Water resource management encounters large variety of multi objective problems that require powerful optimization tools in order to fully characterize the existing tradeoffs between various objectives that can be minimizing difference between forecasted physical, chemical, and biological behaviors of model and measured data. Calibration of complex water quality models for river and reservoir systems may include conflicting objectives addressed by various combinations of interacting calibration parameters. Calibration of the two dimensional CE-QUAL-W2 water quality and hydrodynamic model is an excellent example where the model must be calibrated for both hydrodynamic and water quality behavior. The aim of the present study is to show how multiobjective particle swarm optimization (MOPSO) can be implemented for automatic calibration of water quality and hydrodynamic parameters of a 2-dimensional, hydrodynamic, and water quality models (CEQUAL-W2) to predict physical, chemical, and biological behaviors of a water body, and then focus on a relevant case study. So MOPSO is utilized to generate Pareto optimal solutions for two conflicting calibration objectives. A combined measure of thermal and reservoir water level is considered as the first calibration objective. The second objective is formulated to forecast the best physical, chemical, and biological behavior of the model. Realizing the strong interactions between water quality and hydrodynamic issues of water bodies and their dependencies on the same set of calibration parameters, the proposed multiobjective approach may provide a wide version of all possible calibration solutions for better decision making to select best solution from pareto front.     

Nafion/histidine functionalized carbon nanotube: High-performance fuel cell membranes

Here we show preparation and characterization of a new type of composite membrane based on Nafion^®/histidine modified carbon nanotube by imidazole groups (Im-CNT), for direct methanol fuel cell (DMFC) applications. Due to the presence of this imidazole-based amino acid on the surface of CNT, new electrostatic interactions can be formed in the interface of Nafion^® and Im-CNT. Physical characteristics of these nanocomposite membranes are investigated by water uptake, methanol permeability, ion exchange capacity, proton conductivity, as well as fuel cell performance results.     

Process Mining Approach of a New Water Quality Index for Long-Term Assessment under Uncertainty Using Consensus-Based Fuzzy Decision Support System

One of the biggest challenges in water quality monitoring is how to optimize big Data gathered from a wide range of resources. This paper presented a new software-based pathway of process mining approach for extending a flexible WQI (Water Quality Index) that would deal with uncertainties derived from missing data occurrence in short- and long-term assessments. The methodology is based on integration of four multi-criteria group decision-making models coupled with fuzzy simulation including AHP (Analytical Hierarchy Process), fuzzy OWA (Ordered Weighting Average), TOPSIS (Technique for Order Preference by Similarity to Ideal Solution), and fuzzy TOPSIS that were used for data mining and group consensus evaluation.. Examining the methodology on groundwater resources being supplied for drinking in Shiraz, Iran showed high integrity, accuracy, and proximity-to-real interpretation of water quality. This was the first study where decision-making risks such as Decision Makers’ risk-prone or risk-aversion attitudes (optimistic degree), DMs’ power, and consensus degree of each water quality parameter have been considered in WQI research. The proposed index offered a flexible choice in defining the intended project duration, stakeholders’ judgments, types of water use and water resource, standards, as well as type and number of water quality parameters. Thus, beside sustaining the unity in structure, this methodology could be suggested as a potentially WQI for other regions. The presented methodology would help more efficient monitoring of water resources for drinking purpose with respect to water quality.

     

A Probabilistic Multiperiod Simulation–Optimization Approach for Dynamic Coastal Aquifer Management

Combined simulation–optimization (CSO) schemes are common in the literature to solve different groundwater management problems, and CSO is particularly well-established in the coastal aquifer management literature. However, with a few exceptions, nearly all previous studies have employed the CSO approach to derive static groundwater management plans that remain unchanged during the entire management period, consequently overlooking the possible positive impacts of dynamic strategies. Dynamic strategies involve division of the planning time interval into several subintervals or periods, and adoption of revised decisions during each period based on the most recent knowledge of the groundwater system and its associated uncertainties. Problem structuring and computational challenges seem to be the main factors preventing the widespread implementation of dynamic strategies in groundwater applications. The objective of this study is to address these challenges by introducing a novel probabilistic Multiperiod CSO approach for dynamic groundwater management. This includes reformulation of the groundwater management problem so that it can be adapted to the multiperiod CSO approach, and subsequent employment of polynomial chaos expansion-based stochastic dynamic programming to obtain optimal dynamic strategies. The proposed approach is employed to provide sustainable solutions for a coastal aquifer storage and recovery facility in Oman, considering the effect of natural recharge uncertainty. It is revealed that the proposed dynamic approach results in an improved performance by taking advantage of system variations, allowing for increased groundwater abstraction, injection and hence monetary benefit compared to the commonly used static optimization approach.