Structural Optimization of Hot Water-Cooling Proces...

Jo Jan 17, 2025

Nowadays, main facilities used in heavy industry, including metallurgical, chemical and power generation industries, all use a large amount of heat energy, and they usually have water-cooling systems. A water cooling system has many advantages including its simple structure and low maintenance cost, but on the other hand, the use of low-temperature natural water as an input increases water consumption from the water source, which increases the overall operating cost of production process.

To reduce the operating cost, water consumption has to be reduced by introducing more effective water-cooling methods. But there are technical limitations to the minimum water consumption. Besides, as even the minimum water consumption contains a certain amount of potential energy, recycling of hot cooling water is very important to reduce the energy consumption level of the whole production process.

Since long ago, natural cooling ponds such as rivers and lakes or artificial cooling ponds have been widely used to recycle the hot water from the output of a water-cooling system. However, due to the low cooling effect of traditional cooling ponds and the limited ratio of land occupation, extra cooling facilities are needed.

Introducing high-efficiency cooling ponds to further raise the cooling effect is a good way of reducing the surface area of cooling ponds and energy consumption for urban and other businesses on the limited surface area. Introduction of high-efficiency cooling ponds needs a methodolgy to uniquely design the structure and determine reasonable structural parameters that could satisfy the local climatic and geologic conditions.

Sin Sok Chol, a researcher at the Faculty of Metal Engineering, has proposed a concept of sectional cooling pond (SCP) of simple sectional region structure to raise the hot water-cooling effect without any extra cooling facilities and energy consumption.

In addition, he has conducted a mathematical modeling and CFD analysis of the recycling process of cooling water in the SCPs, thus proving their cooling effects and providing a way of determining reasonable structural parameters for them.

Introduction of SCPs enables recycling of cooling water required by production processes without the need for additional surface area and cooling equipment and energy consumption.

A Method for Learning Speed Improvement of Neural N...

Jo Jan 15, 2025

Forward neural networks are the most common neural networks in a neural network structure, for transmitting signals from input layers to output layers in one direction. In the feedforward neural network, there is no recursive coupling in the hidden layer. This feedforward neural network can simulate complex nonlinear relationships based on training data sets and it has a wide range of applications. In recent years, the feedforward neural network has been applied to many fields such as pattern recognition, decision making, future prediction and inaccessible object simulation. Currently, there is a growing interest in improving convergence and generalization ability in the application of feedforward neural networks.

With increasing researches on convolutional neural networks, the image recognition performance has been greatly improved. Convolutional neural networks have a structure for extracting the features of data by combining multiple convolutional layers with local filtering characteristics. Convolutional neural networks have been used to solve many problems such as satellite image analysis, object detection in natural images, face recognition, object recognition, etc.

Recently, sparse representations have attracted a lot of attention in the field of pattern recognition. The study of sparse representations has been carried out for nearly a century and they have been applied to various fields. In particular, the signal processing sector has aroused interest in sparse representations for compression and interpretation of speech, images and animations in the last decade.

Previous works presented a sparse matrix generation method by singular value decomposition, i.e, k-SVD algorithm. This algorithm increases the order of the dictionary matrix by no less than that of the measurement matrix, which leads to a higher number of iterations and a lower computational efficiency. Thus, it is not suitable for high-dimensional measurement signal processing.

Hwang Chol Hyon, a section head at the Faculty of Information Science and Technology, has studied a sparse representation computation method by singular value decomposition that updates several column data at a time, and proposed an improved k-SVD algorithm. In addition, he has constructed a three-layer BP neural network using the sparse representation calculation procedure of multiple measurement vectors, and implemented the feature extraction of multiple measurement vectors.

The feature extraction method with sparse representation can improve the coupling characteristics of neural network, thus greatly improving the learning speed.

Determination of Stability Conditions for Productio...

Jo Jan 14, 2025

Water is an important basic material in the chemical industry and indispensable for human life. The world has witnessed a lot of progress in the research on the disinfection of water, which is closely related to the human life.

Generally, sterilizers used for water disinfection and wastewater treatment contain chlorine, hydrogen chloride, chlorine dioxide, ozone, hydrogen peroxide and ferrate. These sterilizers have been degraded due to the high cost and the release of substances harmful to the human body. In addition, their low disinfection effectiveness and short duration restrict their usage.

At present, there is a worldwide research to develop new chemical water treatment reagents with a strong disinfection effect and no harm to the human body, especially with a focus on potassium ferrate, one of the green multifunctional water treatment reagents.

Currently, commonly accepted methods for producing potassium ferrate include melting, electrolysis and wet methods. Among them, the wet methods are most widely used since the electrolytic and melting methods have some disadvantages such as high production cost, high power consumption and explosion risk.

One of the most important problems arising in the production of potassium ferrate is that it is stable in dry air but very unstable in aqueous or humid environments and it is easily decomposed. It is rapidly decomposed to release oxygen in acidic solutions and slowly decomposed in neutral or weak basic solutions. The rate of decomposition decreases as the salinity of the solution increases.

The main focus of the research on the production of potassium ferrate is to maximize its stability.

Ri Su Ryon, a researcher at the Faculty of Chemical Engineering, has examined the stability of the production of potassium ferrate widely used for water disinfection by using KI, K₂SiO₃ and K₃PO₄ as stabilizers. The experimental results show that the production of potassium ferrate is stabilized most when the amounts of KI, K₂SiO₃ and K₃PO₄ are 0.1%, 0.4%, and 0.4% of the total amount of reactants, respectively. She has also found that having dimethyl sulfoxide, methanol, diethyl ether as a detergent, it is effective to dehydrate first by using dimethyl sulfoxide and, subsequently remove the impurities such as KCl and KOH by using methanol before finally removing the remaining water and methanol by using diethyl ether. It has also been proved that when the washing temperature is lower than 20℃ and the number of washing is three, the potassium ferrate can be kept for a long time.