Toward intelligent transient stability enhancement in inverter-based microgrids

Neural Computing and Applications - Nowadays, the concept of multiple inverter-interfaced distributed generations (IIDGs)-based MG is recognized as a renowned notion. Encountering unexpected...     

Flexible skew-symmetric shape model for shape representation, classification, and sampling.

Skewness of shape data often arises in applications (e.g., medical image analysis) and is usually overlooked in statistical shape models. In such cases, a Gaussian assumption is unrealistic and a formulation of a general shape model which accounts for skewness is in order. In this paper, we present a novel statistical method for shape modeling, which we refer to as the flexible skew-symmetric shape model (FSSM). The model is sufficiently flexible to accommodate a departure from Gaussianity of the data and is fairly general to learn a "mean shape" (template), with a potential for classification and random generation of new realizations of a given shape. Robustness to skewness results from deriving the FSSM from an extended class of flexible skew-symmetric distributions. In addition, we demonstrate that the model allows us to extract principal curves in a point cloud. The idea is to view a shape as a realization of a spatial random process and to subsequently learn a shape distribution which captures the inherent variability of realizations, provided they remain, with high probability, within a certain neighborhood range around a mean. Specifically, given shape realizations, FSSM is formulated as a joint bimodal distribution of angle and distance from the centroid of an aggregate of random points. Mean shape is recovered from the modes of the distribution, while the maximum likelihood criterion is employed for classification.     

A new intelligent algorithm for dynamic facility layout problem in state of fuzzy constraints

In the present paper, the dynamic facilities layout problem is studied in presence of ambiguity of information flow. Product demand (and consequently material flow) is defined as fuzzy numbers with different membership functions. The problem is modeled in fuzzy programming. Three models of expected value, chance-constrained programming and dependent-chance programming and two hybrid intelligent algorithms are then presented. At the end, efficiency of algorithms for solving fuzzy models of dynamic facilities layout is shown through some numerical examples.     

Interval‐valued Pythagorean fuzzy GRA method for multiple‐attribute decision making with incomplete weight information

In this paper, the concept of multiple‐attribute group decision‐making (MAGDM) problems with interval‐valued Pythagorean fuzzy information is developed, in which the attribute values are interval‐valued Pythagorean fuzzy numbers and the information about the attribute weight is incomplete. Since the concept of interval‐valued Pythagorean fuzzy sets is the generalization of interval‐valued intuitionistic fuzzy set. Thus, due the this motivation in this paper, the concept of interval‐valued Pythagorean fuzzy Choquet integral average (IVPFCIA) operator is introduced by generalizing the concept of interval‐valued intuitionistic fuzzy Choquet integral average operator. To illustrate the developed operator, a numerical example is also investigated. Extended the concept of traditional GRA method, a new extension of GRA method based on interval‐valued Pythagorean fuzzy information is introduced. First, utilize IVPFCIA operator to aggregate all the interval‐valued Pythagorean fuzzy decision matrices. Then, an optimization model based on the basic ideal of traditional grey relational analysis (GRA) method is established, to get the weight vector of the attributes. Based on the traditional GRA method, calculation steps for solving interval‐valued Pythagorean fuzzy MAGDM problems with incompletely known weight information are given. The degree of grey relation between every alternative and positive‐ideal solution and negative‐ideal solution is calculated. To determine the ranking order of all alternatives, a relative relational degree is defined by calculating the degree of grey relation to both the positive‐ideal solution and negative ideal solution simultaneously. Finally, to illustrate the developed approach a numerical example is to demonstrate its practicality and effectiveness.     

An efficient method of designing dual‐ and wide‐band power dividers with arbitrary power division

Capability of microstrip nonuniform transmission lines (MNTLs) for construction of dual‐band and broadband unequal Wilkinson power dividers with arbitrary‐way, arbitrary frequency band operations, and arbitrary power divisions is evaluated. Also, the MNTL transformers are introduced for dual‐band/broadband matching of the unequal output impedances of the MNTL power divider with arbitrary output terminal impedances. The strip width of MNTLs is considered variable and is written as a truncated Fourier series expansion. To show the validity of the design procedure, three experimental MNTL Wilkinson power dividers, which are dual‐band two‐ and three‐way power dividers with different power divisions working at 1 and 3.4 GHz and one broadband equal power divider working from 0.4 to 1.8 GHz, have been designed and fabricated. In the first ones with power division of 1.5, outputs isolation and ports matching of less than ?30 dB are achieved. Next, an extended recombinant structure is presented for achieving three‐way MNTL power dividers with dual‐band operation. The measured isolation between outputs and ports matching are better than 30 dB and measured forward transmissions are between ?4.87 and ?5.45 in two passbands of the divider. Also, for the proposed broadband divider, the measured isolation between the outputs is better than 13 dB in 127% desired bandwidth. © 2012 Wiley Periodicals, Inc. Int J RF and Microwave CAE, 2013.     

Multi-objective optimization of a hatchback rear end utilizing fractional factorial design algorithm

Air flow has significant effects on fuel consumption, performance, and comfort. Decreasing drag coefficient enhances fuel consumption and vehicle performance. Moreover, omitting or reducing the power of aerodynamic noise sources provides passengers comfort. In this paper, optimization of a hatchback rear end is conducted considering drag and aerodynamic noise objectives. To this end, five geometrical parameters of the hatchback rear end are chosen as design variables in two levels. Numerical simulation is applied to survey air flow features around the models in the wind tunnel. To reduce the number of runs, fraction factorial design algorithm is applied to generate layout of the simulations which decreased the number of case studies to half. Main and interaction effects of these factors on drag coefficient and acoustic power of the rear end source are derived using analysis of variance. Optimum level for each parameter is chosen considering simultaneous drag and noise goals. Finally, characteristics of air flow and acoustic power around optimum model are discussed.

     

An Experimental Investigation on the Copper Recovery from Flotation Tailing Dams by Reflotation

In this study, the possibility of copper recovery from flotation tailing of Mazraeh copper mine was investigated. Magnetic separation method was used for concentration of non-magnetic minerals, especially copper bearing minerals, from iron minerals. As a result, copper grade increased up to 0.18% and its recovery reached 86%. Due to mineral’s oxidized surface, accompanied oxide minerals and large quantities of fine particles (i.e. about 80% and 57% were finer than 37 and 15 μm in the sample, respectively), flotation of copper was very difficult. In this regard, the effects of important factors including solution pH, type and collector dosage, dispersant, impeller speed, type of frother, percent solid and surface sulfurization were studied. It was concluded that copper recovery of 52% and copper grade of 2.7% could be obtained under following conditions: pH: 11, Collector: Z11 with 40 g/t, Impeller speed: 1400 rpm, Frother: A65, percent solid: 10% and surface sulfurization by Na₂S with 1000 g/t. On the other hand, the addition of sodium silicate as a dispersant showed a negative effect on the flotation performance.     

Characterization of indoor sources of fine and ultrafine particles: a study conducted in a full-scale chamber

Humans and their activities are known to generate considerable amounts of particulate matter indoors. Some of the activities are cooking, smoking and cleaning. In this study 13 different particle sources were for the first time examined in a 32 m3 full-scale chamber with an air change rate of 1.7 +/- 0.1/h. Two different instruments, a condensation particle counter (CPC) and an optical particle counter (OPC) were used to quantitatively determine ultrafine and fine particle emissions, respectively. The CPC measures particles from 0.02 microm to larger than 1.0 microm. The OPC was adjusted to measure particle concentrations in eight fractions between 0.3 and 1.0 microm. The sources were cigarette side-stream smoke, pure wax candles, scented candles, a vacuum cleaner, an air-freshener spray, a flat iron (with and without steam) on a cotton sheet, electric radiators, an electric stove, a gas stove, and frying meat. The cigarette burning, frying meat, air freshener spray and gas stove showed a particle size distribution that changed over time towards larger particles. In most of the experiments the maximum concentration was reached within a few minutes. Typically, the increase of the particle concentration immediately after activation of the source was more rapid than the decay of the concentration observed after deactivation of the source. The highest observed concentration of ultrafine particles was approximately 241,000 particles/cm3 and originated from the combustion of pure wax candles. The weakest generation of ultrafine particles (1.17 x 10(7) particles per second) was observed when ironing without steam on a cotton sheet, which resulted in a concentration of 550 particles/cm3 in the chamber air. The highest generation rate (1.47 x 10(10) particles per second) was observed in the radiator test. PRACTICAL IMPLICATIONS: Humans and their activities are known to generate substantial amounts of particulate matter indoors and potentially they can have a strong influence on short-term exposure. In this study a quantitative determination of the emissions of fine and ultrafine particles from different indoor sources was performed. The aim is a better understanding of the origin and fate of indoor particles. The results may be useful for Indoor Air Quality models.