Hygrothermal Fracture Analysis of Orthotropic Materials Using J k -Integral

A new computational method based on the J _k -integral is put forward for the purpose of conducting fracture analysis of orthotropic materials subjected to hygrothermal stresses. By utilizing the constitutive relations of plane orthotropic hygrothermoelasticity, an alternative expression for the J _k -integral is derived to replace the general limit definition. A numerical procedure is developed and integrated into a finite element analysis software to implement the proposed form of the J _k -integral. Temperature and specific moisture concentration fields, which are required in fracture calculations, are also computed through finite element analysis. Numerical results are generated by considering an embedded crack in a polymer matrix fibrous composite laminate, that is subjected to steady-state hygrothermal loading. Comparisons of the mixed-mode stress intensity factors computed by the J _k -integral based method to those evaluated via the displacement correlation technique demonstrate that, the proposed form of the J _k -integral is domain independent and leads to numerical results of high accuracy. Presented parametric analyses illustrate the influences of the fiber volume fraction and the crack location on the modes I and II stress intensity factors, the energy release rate, and the T-stress.     

Predicting the settling velocity of flocs formed in water treatment using multiple fractal dimensions

Here we introduce a distribution of floc fractal dimensions as opposed to a single fractal dimension value into the floc settling velocity model developed in earlier studies. The distribution of fractal dimensions for a single floc size was assumed to cover a range from 1.9 to 3.0. This range was selected based on the theoretically determined fractal dimensions for diffusion-limited and cluster-cluster aggregation. These two aggregation mechanisms are involved in the formation of the lime softening flocs analyzed in this study. Fractal dimensions were generated under the assumption that a floc can have any value of normally distributed fractal dimensions ranging from 1.9-3.0. A range of settling velocities for a single floc size was calculated based on the distribution of fractal dimensions. The assumption of multiple fractal dimensions for a single floc size resulted in a non-unique relationship between the floc size and the floc settling velocity, i.e., several different settling velocities were calculated for one floc size. The settling velocities calculated according to the model ranged from 0 to 10 mm/s (average 2.22 mm/s) for the majority of flocs in the size range of 1-250 μm (average 125 μm). The experimentally measured settling velocities of flocs ranged from 0.1 to 7.1 mm/s (average 2.37 mm/s) for the flocs with equivalent diameters from 10 μm to 260 μm (average 124 μm). Experimentally determined floc settling velocities were predicted well by the floc settling model incorporating distributions of floc fractal dimensions calculated based on the knowledge of the mechanisms of aggregation, i.e., cluster-cluster aggregation and diffusion-limited aggregation.     

Methodology for spatio‐temporal predictions of traffic counts across an urban road network and generation of an on‐road greenhouse gas emission inventory

On‐road emission inventories in urban areas have typically been developed using traffic data derived from travel demand models. These approaches tend to underestimate emissions because they often only incorporate data on household travel, not including commercial vehicle movements, taxis, ride hailing services, and other trips typically underreported within travel surveys. In contrast, traffic counts embed all types of on‐road vehicles; however, they are only conducted at selected locations in an urban area. Traffic counts are typically spatially correlated, which enables the development of methods that can interpolate traffic data at selected monitoring stations across an urban road network and in turn develop emission estimates. This paper presents a new and universal methodology designed to use traffic count data for the prediction of periodic and annual volumes as well as greenhouse gas emissions at the level of each individual roadway and for multiple years across a large road network. The methodology relies on the data collected and the spatio‐temporal relationships between traffic counts at various stations; it recognizes patterns in the data and identifies locations with similar trends. Traffic volumes and emissions prediction can be made even on roads where no count data exist. Data from the City of Toronto traffic count program were used to validate the output of various algorithms, indicating robust model performance, even in areas with limited data.     

Preparation and characterization of poly(vinyl chloride)/polystyrene/poly(ethylene glycol) hollow‐fiber ultrafiltration membranes

Hollow‐fiber ultrafiltration (UF) membranes were prepared from blends of poly(vinyl chloride) (PVC) and polystyrene (PS) with a dry/wet phase inversion method. Poly(ethylene glycol) (PEG) and N,N‐dimethylacetamide were used as the additive and solvent, respectively. The effects of the PEG concentration in the dope solution as an additive on the cross sections and inner and outer surface morphologies, permeability, and separation performance of the hollow fibers were examined. The mean pore size, pore size distribution, and mean roughness of both the inner and outer surfaces of the produced hollow fibers were determined by atomic force microscopy. Also, the mechanical properties of the hollow‐fiber membranes were investigated. UF experiments were conducted with aqueous solutions of poly(vinyl pyrrolidone) (PVP; K‐90, M_w = 360 kDa). From the results, we found that the PVC/PS hollow‐fiber membranes had two layers with a fingerlike structure. These two layers were changed from a wide and long to a thin and short morphology with increasing PEG concentration. A novel and until now undescribed shape of the nodules in the outer surfaces, which was denoted as a sea‐waves shape, was observed. The outer and inner pore sizes both increased with increasing PEG concentration. The water permeation flux of the hollow fibers increased from 104 to 367 L m^?2 h^?1 bar^?1) at higher PEG concentrations. The PVP rejection reached the highest value at a PEG concentration of 4 wt %, whereas at higher values (from 4 to 9 wt %), the rejection decreased. The same trend was found also for the tensile stress at break, Young's modulus, and elongation at break of the hollow fibers. © 2013 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 130: 989‐1004, 2013     

Influence of prior cold working on the tribological behavior of Cu–0.65 wt.%Cr alloy

The influence of prior cold working on the friction and wear behavior of Cu–0.65 wt.%Cr alloy under dry sliding against a steel disk was investigated on a pin-on-disk wear tester. The worn surfaces and debrises of Cu–Cr alloy were analyzed by scanning electron microscope (SEM) and energy dispersive X-ray (EDX) spectrum. The results indicated that prior cold working and aging had an effect on the hardness and wear resistance of Cu–Cr alloy; in other words hardness and wear rate increased with the amount of cold working. At constant aging temperature, the wear rate of Cu–Cr alloys increase with cold working and reached maximum at 50% cold working. At constant amount of cold working aged specimens at 500 °C shows higher wear resistance than 450 °C. Crack initiation and propagation in the tribolayer and at the interface of subsurface and tribolayer was the dominant mechanism during the sliding process.     

The effect of sliding speed and amount of loading on friction and wear behavior of Cu–0.65 wt.%Cr alloy

Friction and wear behavior of a peak aged Cu–0.65 wt.%Cr alloy was investigated. The friction and wear experiments were run under ambient conditions with a pin-on-disk tribometer. Experiments were performed using various applied normal loads and sliding velocities. The tribological behavior of the studied alloy was discussed in terms of friction coefficient, wear loss and wear mechanism.Friction coefficient and wear loss have shown large sensitivity to the applied normal load and the sliding velocity. At the sliding velocity of 0.3 m/s weight loss increased from 6.9 to 51 mg by increasing the normal load from 20 to 40 N. At higher sliding velocity minimum weight loss is achieved at 60 N normal load. So it can be seen that with increasing normal load wear rate decreases due to the formation of a continuous tribofilm which consists of Fe–Cu intermetallic. Varying of friction coefficients in different conditions of normal load and sliding velocity is correlated to the wear behavior.The analysis of worn surfaces by XRD and SEM showed that an increase in normal load and sliding velocity creates an intermetallic wear-induced layer, which modifies the wear behavior of the alloy. The XRD result indicates that new phase of Cu_9.9Fe_0.1 is generated on worn surfaces of the pin specimens during the wear tests. There is a significant correlation between the micrograph of worn surfaces and the wear rate of specimens.     

Dry-or-buy decision support for dry kiln scheduling in furniture production

In this paper, a dry-or-buy cost model for a dry kiln scheduling problem in the furniture manufacturing industry is considered. Factory-specified due-dates for jobs, kiln availability, kiln capacity, and drying and buying costs are incorporated into an Integer-Programming (IP) model. As it may be difficult (i.e., because of due-dates, kiln availability, processing times, etc.) to meet all the due-dates, certain jobs may have to be out-sourced. The objective of the model is to minimize the total drying and buying costs while satisfying all due-dates. Because of the computational complexity of the problem, a heuristic approach is developed. Computational experience indicates that the heuristic gives high quality solutions with significant savings in time over standard IP algorithms.     

Recyclable,Flexible, Low‐Power Oxide Electronics

The ability to process and dimensionally scale field‐effect transistors with and on paper and to integrate them as a core component for low‐power‐consumption analog and digital circuits is demonstrated. Low‐temperature‐processed p‐ and n‐channel integrated oxide thin‐film transistors in the complementary metal oxide semiconductor (CMOS) inverter architecture are seamlessly layered on mechanically flexible, low‐cost, recyclable paper substrates. The possibility of building these circuits using low‐temperature processes opens the door to new applications ranging from smart labels and sensors on clothing and packaging to electronic displays printed on paper pages for use in newspapers, magazines, books, signs, and advertising billboards. Because the CMOS circuits reported constitute fundamental building blocks for analog and digital electronics, this development creates the potential to have flexible form factor computers seamlessly layered onto paper. The holistic approach of merging low‐power circuitry with a recyclable substrate is an important step towards greener electronics.     

Incorporating microgrids coupling with utilization of flexible switching to enhance self-healing ability of electric distribution systems

Electric distribution networks have to deal with issues caused by natural disasters. These problems possess unique characteristics, and their severity can make load restoration methods impotent. One solution that can help in alleviating the aftermath is the use of microgrids (MGs). Employing the cumulative capacity of the generation resources through MG coupling facilitates the self-healing capability and leads to better-coordinated energy management during the restoration period, while the switching capability of the system should also be considered. In this paper, to form and schedule dynamic MGs in distribution systems, a novel model based on mixed-integer linear programming (MILP) is proposed. This approach employs graph-related theories to formulate the optimal formation of the networked MGs and management of their proper participation in the load recovery process. In addition, the Benders decomposition technique is applied to alleviate computability issues of the optimization problem. The validity and applicability of the proposed model are evaluated by several simulation studies.     

Event‐triggered optimal tracking control of nonlinear systems

We propose a novel event‐triggered optimal tracking control algorithm for nonlinear systems with an infinite horizon discounted cost. The problem is formulated by appropriately augmenting the system and the reference dynamics and then using ideas from reinforcement learning to provide a solution. Namely, a critic network is used to estimate the optimal cost while an actor network is used to approximate the optimal event‐triggered controller. Because the actor network updates only when an event occurs, we shall use a zero‐order hold along with appropriate tuning laws to encounter for this behavior. Because we have dynamics that evolve in continuous and discrete time, we write the closed‐loop system as an impulsive model and prove asymptotic stability of the equilibrium point and Zeno behavior exclusion. Simulation results of a helicopter, a one‐link rigid robot under gravitation field, and a controlled Van‐der‐Pol oscillator are presented to show the efficacy of the proposed approach. Copyright © 2016 John Wiley & Sons, Ltd.