Experimental investigation of continuous conductivity measurements during emulsion polymerizations having unstable/high‐fouling reaction mixture

Conductimetry is one of the online monitoring techniques employed for emulsion polymerization reactions, which can give continuous information about nucleation and growth of particles. The most important factor affecting conductivity sensors performance especially contacting (resistance) types is fouling. To investigate the consequences of fouling, four monomers with different tendencies for fouling were selected: methyl methacrylate, butyl acrylate, styrene, and butadiene. Two types of conductivity sensors were also selected to continuously measure conductivity: a two‐electrode sensor and an inductive sensor, and the performance of these sensors were evaluated based on some criteria such as conductivity behavior, amount of fluctuation, change in cell constant, repeatability, and status of the minimum of conductivity. The results obtained from the contacting sensor showed that fouling significantly decreased the performance of this sensor in different ways even in reaction mixtures having moderate fouling rates. However, the inductive conductivity sensor provided the possibility of reliably measuring conductivity during very high‐fouling and highly unstable emulsion polymerizations with very good repeatability. The capabilities of this sensor also allowed an exact recognition of the important points in the conductivity curves particularly the minimum of conductivity. © 2016 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2017 , 134, 44446.     

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.     

Interactions between shrinkage reducing admixtures (SRA) and cement paste's pore solution

Shrinkage reducing admixtures (SRA) have been developed to combat shrinkage cracking in concrete elements. While SRA has been shown to have significant benefits in reducing the magnitude of drying and autogenous shrinkage, it has been reported that SRA may cause a negative side effect as it reduces the rate of cement hydration and strength development in concrete. To examine the influence of SRA on cement hydration, this study explores the interactions between SRA and cement paste's pore solution. It is described that SRA is mainly composed of amphiphilic (i.e., surfactant) molecules that when added to an aqueous solution, accumulate at the solution-air interface and can significantly reduce the interfacial tension. However, these surfactants can also self-aggregate in the bulk solution (i.e., micellation) and this may limit the surface tension reduction capacity of SRA. In synthetic pore solutions, SRA is observed to form an oil-water-surfactant emulsion that may or may not be stable. Specifically, at concentrations above a critical threshold, the mixture of SRA and pore fluid is unstable and can separate into two distinct phases (an SRA-rich phase and an SRA-dilute phase). Further, chemical analysis of extracted pore solutions shows that addition of SRA to the mixing water depresses the dissolution of alkalis in the pore fluid. This results in a pore fluid with lower alkalinity which causes a reduction in the rate of cement hydration. This may explain why concrete containing SRA shows a delayed setting and a slower strength development.     

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.     

Investigation of pointed domes—II. Experiment

The aim of the experiment was to study the behavior of pointed domes subjected to point loading at the vertex. A concrete dome reinforceed with 1 mm bars running both in the meridional and parallel circular direction was constructed. Electrical resistance strain gages were mounted at several locations along the meridional and parallel direction of the shell both inside and outside. The structure was loaded within the elastic limit.The experimental values of membrane stress field are calculated and compared with the theoretical values as is described in part I of this report. (see pp. 81–85). These results are in close agreement in regions some distance away from the lower boundary and the pointed apex. But the difference between the two results becomes noticeable near the lower boundary and the vertex of the dome. Further analysis of the experiment findings indicates that the bending strain field is slight at regions that are some distance away from the lower boundary and to the apex of the dome.     

A charge sharing–based switching scheme for SAR ADCs

This paper presents an energy-efficient switching scheme for successive approximation register (SAR) analogue-to-digital converter (ADC). The proposed scheme employs charge recycling method to keep the capacitor arrays free of transitional energy between bit generations except reset phase. In comparison with the conventional switching scheme, the proposed one achieves 100% transitional energy saving without considering reset phase. In addition, configuration of a 10-bit SAR ADC shows that the proposed switching scheme reduces the capacitor area by 25% compared with the conventional switching scheme.     

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.     

Fractional-order unstable pole-zero cancellation in linear feedback systems

As a very well-known classical fact, non-minimum phase zeros of the process put some limitations on the performance of the feedback system. The source of these limitations is that non-minimum phase zeros cannot be cancelled by unstable poles of the controller since such a cancellation leads to internal instability. The aim of this paper is to propose a method for fractional-order cancellation of non-minimum phase zeros of the process and studying its properties. It is specially shown that the proposed cancellation strategy increases the phase and gain margin without leading to internal instability. Since the systems with higher gain and phase margin are easier to control, the proposed method can be used to arrive at more effective controls, which is also verified by the simulation results.     

A GMM/HMM model for reconstruction of missing speech spectral components for continuous speech recognition

This paper presents a method for reconstructing unreliable spectral components of speech signals using the statistical distributions of the clean components. Our goal is to model the temporal patterns in speech signal and take advantage of correlations between speech features in both time and frequency domain simultaneously. In this approach, a hidden Markov model (HMM) is first trained on clean speech data to model the temporal patterns which appear in the sequences of the spectral components. Using this model and according to the probabilities of occurring noisy spectral component at each states, a probability distributions for noisy components are estimated. Then, by applying maximum a posteriori (MAP) estimation on the mentioned distributions, the final estimations of the unreliable spectral components are obtained. The proposed method is compared to a common missing feature method which is based on the probabilistic clustering of the feature vectors and also to a state of the art method based on sparse reconstruction. The experimental results exhibits significant improvement in recognition accuracy over a noise polluted Persian corpus.