Quantifying the effects of crack width,tortuosity, and roughness on water permeability of cracked mortars

The existing service-life prediction models rarely account for the effect of cracks on mass transport and durability of concrete. To correct this deficiency, transport in fractured porous media must be studied. The objective of this paper is to quantify the water permeability of localized cracks as a function of crack geometry (i.e., width, tortuosity, and surface roughness). Plain and fiber-reinforced mortar disk specimens were cracked by splitting tension; and the crack profile was digitized by image analysis and translated into crack geometric properties. Crack permeability was measured using a Darcian flow-thru cell. The results show that permeability is a function of crack width square. Crack tortuosity and roughness reduce the permeability by a factor of 4 to 6 below what is predicted by the theory for smooth parallel plate cracks. Although tortuosity and roughness exhibit fractal behavior, their proper measurement is possible and results in correct estimation of crack permeability.     

The characteristics of hot mixed asphalt modified by nanosilica

The objective of this research is to investigate the characteristics of the hot mixed asphalt modified by 2%, 4%, 6%, and 8% nanosilica by weight of binder. Marshall stability, dynamic creep, and indirect tensile tests were used to study effects of nanosilica on performance characteristics of the mixtures. Results showed that nanosilica can improve Marshall stability, resilient modulus, indirect tensile strength, and fatigue life compared to unmodified mixtures. However, the tensile strength ratio parameter in the moisture sensitivity tests indicated a decrease in the resistance of the modified mixtures against moisture damage.     

A music symbols recognition method using pattern matching along with integrated projection and morphological operation techniques

Multimedia Tools and Applications - Optical Music Recognition (OMR) can be divided into three main phases: (i) staff line detection and removal. The goal of this phase is to detect and to remove...     

Fabrication and Characterization of Functionally Graded Al/SiCp Composites Produced by Remelting and Sedimentation Process

A new process termed here as remelting and sedimentation (RAS) was developed to produce functionally graded Al/SiC composites with a smooth concentration gradient of SiC particles along the height of samples, as opposed to a step change. For this purpose, first settling velocities of different-sized SiC particles in aluminum A356 melt were measured, and the results exhibited a reasonably good agreement with those predicted via the modified Stokes law. Then slices of particulate Al/SiC composites with different SiC contents of 5, 10, 15, and 20 vol.% were stacked in a cast iron mold and heated at 650 °C resulting in remelting and unification of the different composite parts. Considering the preliminary settling experiments, the composite slurry was held at this temperature for three different times to investigate the optimum holding time for obtaining a smooth gradient of SiC concentration along the height of the sample. After quenching, the samples were sectioned and subjected to metallographic studies and hardness measurements. The results confirmed that holding the melt for 60 s provides sufficient settling and redistribution of SiC particles and results in successful production of a functionally graded material.     

Incremental labeling in closed-2PM model

We consider an incremental optimal label placement in a closed-2PM map containing points each attached with a label. Labels are assumed to be axis-parallel square-shaped and have to be pairwise disjoint with maximum possible length each attached to its corresponding point on one of its horizontal edges. Such a labeling is denoted as optimal labeling. Our goal is to efficiently generate a new optimal labeling for all points after each new point being inserted in the map. Inserting each point may require several labels to flip or all labels to shrink. We present an algorithm that generates each new optimal labeling in O(lgn+k) time where k is the number of required label flips, if there is no need to shrink the label lengths, or in O(n) time when we have to shrink the labels and flip some of them. The algorithm uses O(n) space in both cases. This is a new result on this problem.     

Using backward elimination with a new model order reduction algorithm to select best double mixture model for document clustering

Probabilistic latent semantic analysis (PLSA) is a double structure mixture model which has got a wide application in text and web mining. This method is capable of establishing hidden semantic relations among the observed features, using a number of latent variables. In this approach, the selection of the correct number of latent variables is critical. In the most of the previous researches, the number of latent topics was selected based on the number of invoked classes. This paper presents a method, based on backward elimination approach, which is capable of unsupervised order selection in PLSA. This method starts with a model having a number of components more than the needed value, and then prunes the mixtures to reach their optimum size. During the elimination process, proper selection of some latent variables which must be deleted is the most essential problem, and its relation to the final performance of the pruned model is straightforward. To treat this problem, we introduce a new combined pruning method which selects the best options for removal, while keeping a low computational cost, at all. We conducted some experiments on two datasets from Reuters-21578 corpus. The obtained results show that this algorithm leads to an optimized number of latent variables and in turn achieves better clustering performance compared to the conventional model selection methods. It also shows superiority over the case in which a PLSA model with a fixed number of latent variables, equal to the real number of clusters, is exploited.     

IPS-MAC: an informative preamble sampling MAC protocol for wireless sensor networks

Radio transceivers are the main source of energy consumption in wireless sensor networks (WSNs) where the source of energy supply is non-rechargeable battery. Several MAC protocols have been proposed in order to efficiently conserve energy in the link layer via duty-cycling. Low power listening (LPL) methods have been shown to outperform other schemes in lightly loaded situations which are common in environment monitoring applications. Nonetheless, as the network becomes dense, in LPL protocols such as BMAC a large number of nodes stay awake for each transmission, resulting in high levels of energy consumption. This paper introduces the informative preamble sampling (IPS) protocol in which a transmitter implicitly embeds information about its intended receiver via the power at which the preamble is transmitted. This results in far fewer nodes staying awake for each preamble. Upon hearing the preamble, a receiver executes a decision-making algorithm to decide whether to stay awake. If the decision-making algorithm is too lax, then more nodes stay awake following the preamble. On the other hand if the algorithm is too strict, it is likely that the intended receiver misses the preamble. In this paper we derive the optimal operating points for the IPS protocol. We show analytically that the IPS protocol can achieve a gain in energy by at least a factor of 2 over BMAC. We also conduct extensive simulations to show that IPS can achieve significant energy gains compared to BMAC.     

A 2D numerical simulation of sub-cooled flow boiling at low-pressure and low-flow rates

The main purpose of this study is to apply a two-fluid mathematical model to numerical simulation of two-phase flow at low-pressure condition. Although models of sub-cooled boiling flow at one-dimension and high-pressure have been studied extensively, there are few equivalent studies for numerical simulation at two-dimension and low-pressure (1-2 bar) conditions. Recent literature studies on sub-cooled boiling flow at low-pressure have shown that empirical models developed for high-pressure situations are not valid at low-pressures. Since the mathematical model used in this study is accomplished at low-pressure, the transport equations for the variables of each phase are substituted in low-pressure. The governing equations of two-phase flow with an allowance to inter-phase transfer of mass, momentum and heat, are solved using a two-fluid; non-equilibrium model. The finite volume discretization scheme is used to create a linearized system of equations that are solved by SIMPLE staggered grid solution technique for a rectangular channel. Improvement of the void fraction prediction of our model for the case of low-pressure sub-cooled flow boiling conditions was achieved. It is found that the heat transfer due to evaporation and surface quenching is higher than that by convection. Good agreement is achieved with the predicted results against the experimental data’s available in the literatures for a number of test cases.