On the rotating elastic–plastic solid disks of variable thickness having concave profiles

In this paper, an analytical solution for the elastic–plastic stress distribution in rotating variable thickness solid disks is presented. The analysis is based on Tresca's yield criterion, its associated flow rule and linear strain hardening material behavior. It is shown that depending on the shape of the disk profile, the radial stress in the central region may exceed the circumferential stress. The plastic zone which develops away from the axis of the disk consists of three annular regions governed by different mathematical forms of the yield criterion. The propagation of these plastic regions with increasing angular velocity is obtained together with the distributions of stresses and deformations in nondimensional forms.     

Expert spindle design system

This paper presents an expert spindle design system strategy which is based on the efficient utilization of past design experience, the laws of machine design, dynamics and metal cutting mechanics. The configuration of the spindle is decided from the specifications of the workpiece material, desired cutting conditions, and most common tools used on the machine tool. The spindle drive mechanism, drive motor, bearing types, and spindle shaft dimensions are selected based on the target applications. The paper provides a set of fuzzy design rules, which lead to an interactive and automatic design of spindle drive configurations. The structural dynamics of the spindle are automatically optimized by distributing the bearings along the spindle shaft. The proposed strategy is to iteratively predict the Frequency Response Function (FRF) of the spindle at the tool tip using the Finite Element Method (FEM) based on the Timoshenko beam theory. The predicted FRF of the spindle is integrated to the chatter vibration stability law, which indicates whether the design would lead to chatter vibration free cutting operation at the desired speed and depth of cut for different flutes of cutters. The arrangement of bearings is optimized using the Sequential Quadratic Programming (SQP) method.     

Solution blowing of thermoplastic polyurethane nanofibers: A facile method to produce flexible porous materials

Solution blowing (SB) is a promising and scalable approach for the production of nanofibers. Air pressure, solution flow‐rate, and nozzle‐collector distance were determined as effective process parameters, while solution concentration was also reported as a material parameter. Here we performed a parametric study on thermoplastic polyurethane/dimethyl formamide (TPU/DMF) solutions to examine the effect of such parameters on the resultant properties such as fiber diameter, diameter distribution, porosity, and air permeability of the nanofibrous webs. The obtained solution blown thermoplastic polyurethane (TPU) nanofibers had average diameter down to 170 ± 112 nm, which is similar to that observed in electrospinning. However, the production rate per nozzle can be 20 times larger, which is primarily dependent on air pressure and solution flow rate (20 mL/h). Moreover, it was even possible to produce nanofibers polymer concentrations of 20%; however, this increased the average nanofiber diameter. The fibers produced from the TPU/DMF solutions at concentrations of 20% and 10% had average diameters of 671 ± 136 nm and 170 ± 112 nm, respectively. SB can potentially be used for the industrial‐scale production of products such as nanofibrous filters, protective textiles, scaffolds, wound dressings, and battery components. © 2015 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2016 , 133, 43025.     

Stability aspects of a multifrequency model of a PWM converter

In this paper the stability of a multifrequency model of a PWM converter is investigated. A multifrequency model is a model based on Fourier series that contains as a special case the so-called state space average model. In contrast to a state space average model a multifrequency model may also include so-called higher order harmonics, where the zeroth order harmonic corresponds to the (moving) average. This paper focuses on a specific PWM converter, namely a ( uk converter, and it is proved that a multifrequency model of a ( uk converter with fixed duty ratio is asymptotically stable. This result generalizes the known corresponding result for a state space average model of a ( uk converter with fixed duty ratio. Taking all the harmonics into account the result also illustrates the well-known fact that a ( uk converter with a fixed duty ratio and a finite switching frequency is asymptotically stable in the following sense. If the signals in a ( uk converter do not correspond with a periodic behaviour, they will however do so in the limit, i.e. as time goes to infinity the signals will become periodic, and this limiting periodic behaviour is unique. Although the paper mainly deals with the stability issues for a ( uk converter, it is possible to use the ideas of the paper to derive similar results for other types of PWM converters.     

Symbiotic organisms search algorithm for dynamic economic dispatch with valve-point effects

Abstract

In this study, symbiotic organisms search (SOS) algorithm is proposed to solve the dynamic economic dispatch with valve-point effects problem, which is one of the most important problems of the modern power system. Some practical constraints like valve-point effects, ramp rate limits and prohibited operating zones have been considered as solutions. Proposed algorithm was tested on five different test cases in 5 units, 10 units and 13 units systems. The obtained results have been compared with other well-known metaheuristic methods reported before. Results show that proposed algorithm has a good convergence and produces better results than other methods.     

A matrix-free quasi-Newton method for solving large-scale nonlinear systems

One of the widely used methods for solving a nonlinear system of equations is the quasi-Newton method. The basic idea underlining this type of method is to approximate the solution of Newton’s equation by means of approximating the Jacobian matrix via quasi-Newton update. Application of quasi-Newton methods for large scale problems requires, in principle, vast computational resource to form and store an approximation to the Jacobian matrix of the underlying problem. Hence, this paper proposes an approximation for Newton-step based on the update of approximation requiring a computational effort similar to that of matrix-free settings. It is made possible by approximating the Jacobian into a diagonal matrix using the least-change secant updating strategy, commonly employed in the development of quasi-Newton methods. Under suitable assumptions, local convergence of the proposed method is proved for nonsingular systems. Numerical experiments on popular test problems confirm the effectiveness of the approach in comparison with Newton’s, Chord Newton’s and Broyden’s methods.     

Modeling the Infiltration Capacity of Permeable Stormwater Channels with a Check Dam System

The use of permeable stormwater channels has introduced concerns over the effects of infiltration on the hydraulic behavior of their flow and the effects of flow hydraulic conditions (e.g., the water level, channel section, flow velocity, and vegetation) on the channel infiltration capacity. A check dam system provides backwater ponding, which increases the flow water depth along a channel. In this study, a channel model was used to investigate the variation in the infiltration capacity of permeable stormwater channels under different flow hydraulic conditions. Increasing the downstream check dam height and using a grass cover increased the infiltration rate and cumulative infiltration because of the decreased velocity and increased flow depth. The presence of subsurface water did not affect the hydraulic characteristics of the channel flow but decreased the cumulative infiltration because of the fast saturation of the soil. An empirical equation was developed for predicting the infiltration capacity of grassed channels in which four hydraulic parameters (i.e., the water depth, base width, side slope, and velocity) are introduced to the modified Kostiakov model. The developed model was used to calculate the runoff reduction due to infiltration along a grassed channel with and without a check dam system. The percentage of infiltrated water increased from 8 to 14% with the check dam system. The developed model can be used to predict the infiltration capacity of permeable channels for improved stormwater management and provides a valuable decision support tool for permeable channel design.

     

Comparison of Rainfall-Runoff Relationship Modeling using Different Methods in a Forested Watershed

The daily rainfall-runoff relationship in an experimental watershed was modeled using a statistical method and an artificial neural network method. The estimations were examined and a performance evaluation was done. It was seen that the ANN method, FFBP (Feed Forward Back Propagation), provided closer flow estimations reproducing the shape of the observed hydrograph more realistic. The superiority of FFBP was reflected in the performance evaluation criteria. The extreme flows, i.e., high and low flows, were relatively better approximated by FFBP indicating its promise as a useful tool for hydrologic studies such as flood modeling. The Rational Method was also used, as a conventional tool, to predict the maximum discharge for selected return periods. It was found to be realistic for the forested watershed under consideration when the C coefficient was taken as 0.20 for the 10-year period.

     

Efficient many-to-many feature matching under the l1 norm

Matching configurations of image features, represented as attributed graphs, to configurations of model features is an important component in many object recognition algorithms. Noisy segmentation of images and imprecise feature detection may lead to graphs that represent visually similar configurations that do not admit an injective matching. In previous work, we presented a framework which computed an explicit many-to-many vertex correspondence between attributed graphs of features configurations. The framework utilized a low distortion embedding function to map the nodes of the graphs into point sets in a vector space. The Earth Movers Distance (EMD) algorithm was then used to match the resulting points, with the computed flows specifying the many-to-many vertex correspondences between the input graphs. In this paper, we will present a distortion-free embedding, which represents input graphs as metric trees and then embeds them isometrically in the geometric space under the l₁ norm. This not only improves the representational power of graphs in the geometric space, it also reduces the complexity of the previous work using recent developments in computing EMD under l₁. Empirical evaluation of the algorithm on a set of recognition trials, including a comparison with previous approaches, demonstrates the effectiveness and robustness of the proposed framework.     

Missing wind data forecasting with adaptive neuro-fuzzy inference system

In any region, to begin generating electricity from wind energy, it is necessary to determine the 1-year distribution characteristics of wind speed. For this aim, a wind observation station must be constructed and 1-year wind speed and direction data must be collected. For determining the distribution characteristics, the collected data must be statistically analyzed. The continuity and reliability of the data are quite important for such studies on the days when possible faults can occur in any part of the observation unit or on days when, the system is on maintenance, it is not possible to record any data. In this study, it is assumed that the station had not worked at some randomly chosen days and that for these days no data could be recorded. The missing data are predicted using the data that were recorded before and after fault or maintenance by an adaptive neuro-fuzzy inference system (ANFIS). It is seen that ANFIS is successful for such a study.