Effects of coal comminution in relation to waterjet and selected feed properties

The necessity to develop a viable alternative to oil means that the development of coal-water fuels (CWF) has become increasingly important. However, the existing methods of comminution to prepare ultrafine particles for CWF are very inefficient. Consequently, a number of novel methods of comminution have been investigated in order to increase the efficiency of the process. In this research, a new method of comminution using a high-pressure waterjet has been tested to produce ultrafine particle sizes necessary for efficient CWF process. To establish the fundamental performance of the waterjet mill, the influence of the operational pressure, standoff distance, feed size, mode (dry/wet) of feed material, and ash content of feed material were evaluated. The comminution products were characterized in terms of particle size, surface area change, particle size distribution (PSD), and morphological properties. The experimental results show that this new comminution method offers a promising means for achieving the size reduction required for use in CWF. It was also found that the waterjet-mediated comminution of coal was strongly affected by all these operating parameters. Higher operational pressure led to finer products that were more spherical shaped, while the energy efficiency of the mill strongly depended on the initial feed size and standoff distance. Since there is currently no accurate mode assessing the size of the comminution products, a volume-based fractal model was deduced to characterize the particle size distribution of the comminution products through a single and exact parameter --Abstract, page iii

Text Coherence Analysis Based on Deep Neural Network

In this paper, we propose a novel deep coherence model (DCM) using a convolutional neural network architecture to capture the text coherence. The text coherence problem is investigated with a new perspective of learning sentence distributional representation and text coherence modeling simultaneously. In particular, the model captures the interactions between sentences by computing the similarities of their distributional representations. Further, it can be easily trained in an end-to-end fashion. The proposed model is evaluated on a standard Sentence Ordering task. The experimental results demonstrate its effectiveness and promise in coherence assessment showing a significant improvement over the state-of-the-art by a wide margin.Comment: 4 pages, 2 figures, CIKM 201

Enhanced Gas-Flow-Induced Voltage in Graphene

We show by systemically experimental investigation that gas-flow-induced voltage in monolayer graphene is more than twenty times of that in bulk graphite. Examination over samples with sheet resistances ranging from 307 to 1600 {\Omega}/sq shows that the induced voltage increase with the resistance and can be further improved by controlling the quality and doping level of graphene. The induced voltage is nearly independent of the substrate materials and can be well explained by the interplay of Bernoulli's principle and the carrier density dependent Seebeck coefficient. The results demonstrate that graphene has great potential for flow sensors and energy conversion devices

A Similarity Detection Method Based on Distance Matrix Model with Row-Column Order penalty Factor

Paper detection involves multiple disciplines, and making a comprehensive and correct evaluation of academic misconduct is quite a complex and sensitive issue. There are some problems in the existing main detection models, such as incomplete segmentation preprocessing specification, impact of the semantic orders on detection, near-synonym evaluation, slow paper backtrack and so on. This paper presents a sentence-level paper similarity comparison model with segmentation preprocessing based on special identifier. This model integrates the characteristics of vector detection, hamming distance and the longest common substring and carries out detection specific to near-synonyms, word deletion and changes in word order by redefining distance matrix and adding ordinal measures, making sentence similarity detection in terms of semantics and backbone word segmentation more effective. Compared with the traditional paper similarity retrieval, the present method adopts modular-2 arithmetic with low computation. Paper detection method with reliability and high efficiency is of great academic significance in word segmentation, similarity detection and document summarization

A Test Case Generation Method for Workflow Systems Based on I/O_WF_Net

At present, the testing of the workflow system is mainly based on manual testing, and the functions of only some tools are relatively simple. The design of test cases mainly depends on the experience of testers, which makes the lack of test coverage. In this paper, a test case generation method based on the I/O_WF_Net model is proposed. A test case generation algorithm that satisfies the process branch coverage criterion is designed, which solves the problem of automatic test case generation for workflow systems. The algorithm divides the model according to "split-merge pairs" to generate a decomposition tree of the model, and then traverses the tree to generate test cases. A workflow system modelling and test case generation tool are designed and implemented, and an actual workflow system is used as the experimental object to verify the effectiveness of the method

Application of the fractal theory for evaluating effects of coal comminution by waterjet

© 2014, The Author(s).Comminution of coal to ultrafine sizes by high-pressure waterjet provides a novel method for preparation of coal-water fuels for next generation, near-zero emission electric power generation. The particle size distribution (PSD) of ground coal is a key parameter in the preparation of slurries as it determines the settling behavior of the particles and viscosity of the coal-water mixture. There are several methods available for representation and evaluation of particle size analysis data. However, fractal theory provides a means by which the entire PSD of comminuted materials can be quantified by using of a specific and exact value. In this paper, a volume-based fractal model was deduced to characterize the PSD of the coal which is ground in a specially designed comminution cell. During the size reduction process, the inlet pressures up to 276 MPa were used