Jo Feb 11, 2025
Mineral waters have been widely used since long ago because of its abundance of natural minerals useful for human life. In recent years, the variety and production of bottled mineral waters have increased rapidly due to water pollution from various causes, depletion of drinking water sources and increasing demand of human for health. An important issue in the production of bottled mineral water is to maintain the physical and chemical characteristics including hygienic safety and color and taste after bottle packaging, for a certain period of time. This encouraged some studies to analyze the microbial status of bottled mineral water and to explain the cause of microbial development and growth.
It is not microorganisms alone that affect the quality of mineral water. Mineral waters also contain unstable components such as iron, manganese and sulfur which are possible to be removed by ozone-rich gases. However, among the inorganic materials in mineral water sources, Fe2+ that fails to undergo sufficient oxidation can be oxidized to Fe3+ during storage of mineral water and become precipitates, which do not change the total iron content in mineral water, but may change the physical properties such as turbidity. Therefore, Fe2+ should be fully oxidized and deposited before the bottling of mineral water to increase the shelf life of mineral water.
Most mineral water, especially with CO2 above 400mg/L-1, has a pH below 7, which might also have a negative effect on ozone treatment of mineral water. In addition, CO2 gas, which is dissolved in mineral water, makes it difficult for other gases to dissolve in mineral water. This is because, according to Henry’s law of solubility, the amount of gas dissolved in water depends on the partial pressure of the gas dissolved in the water. Therefore, effective oxidation and deposition of Fe2+ by using ozone gas in CO2-rich mineral water requires a new method of ozone injection and injection conditions to suit the characteristics of mineral water.
Choe Un Hwa, a researcher at the Faculty of Physical Engineering, has chosen a suitable ozone injection step and proposed a new mineral water treatment method using microbubbles by considering the characteristics of mineral water with a low content of ozone but much CO2.
As a result of the treatment of bottled mineral water with ozone microbubbles, the concentration of the iron ion was reduced from 0.14 to 0.01 mg/L-1, and the shelf life increased to 360 days. During the treatment, the concentrations of K+ and Na+ almost remained unchanged, and the deposition time was reduced to one-third compared to natural oxidation.
You can find the details in her paper “REMOVAL OF DEPOSITS AND IMPROVEMENT OF SHELF LIFE IN CO2-RICH MINERAL WATER BY OZONEMICROBUBBLES” in “QUMICA NOVA” (SCI).
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Jo Feb 10, 2025
Machining process modeling and optimization are two major issues in manufacturing processes. The process modeling and optimization techniques are vital to meet increasing quality demand (high quality, low cost and environmental friendliness) in manufacturing practice. The machining process for a computer numerical controlled (CNC) machine is programmed by process parameters such as cutting speed, feed rate and cutting depth. Traditional trial and error method for determining the machining process parameters based on experience cannot guarantee the optimal machining performance for CNC machines.
Many previous studies on machining processes have applied different modeling, integrating and optimization methods. However, they may have considerable inconsistent and conflicting results, which is one of the drawbacks to be overcome in manufacturing practice.
Ryang Si Ho, a section head at the Faculty of Mechanical Science and Technology, has proposed a multiple performances optimization methodology for computer numerical controlled (CNC) machining based on Taguchi method, multi-criteria decision-making (MCDM) and multiple regression (MR) model.
The proposed method consists of the following steps: (1) setting levels of process parameters and selecting suitable Taguchi orthogonal array (OA), (2) arranging the process parameters on the OA and measuring machining performance values at every trial, (3) calculating comprehensive performance (CP) by integrating the multiple performances using a reasonable MCDM, (4) developing MR model between the CP and the process parameters, (5) analyzing the influence of process parameters based on correlation analysis, and (6) determining the optimal process parameters using grid search method.
In order to verify the effectiveness of the proposed method, he applied it to analysis and determination of the influence and optimal turning process parameters such as cutting speed (CS), feed rate (FR), cutting depth (CD), cutting environment (CE) and tool nose radius (NR) for optimizing four machining performances such as surface roughness (SR), cutting force (CF), tool life (TL) and power consumption (PC) in the high speed CNC turning of AISI P20 tool steel.
For more information, please refer to his paper “A methodology for multiple performances optimization of computer numerical controlled (CNC) machining process based on design of experiment, multi-criteria decision-making and multiple regression model” in “International Journal on Interactive Design and Manufacturing” (SCI).
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Jo Feb 7, 2025
PID control is a very effective control method for industry and more than 95% of controllers for process control are of PID type. It is well-known that the performance of a PID controller depends on the tuning of its parameters. For this reason, a lot of tuning methods have been proposed.
Among them, predictive functional control (PFC) has appeared as a better choice to solve different problems. If the control objective is to improve the behavior of low-order processes, PFC is a good choice because of the simplicity of both algorithm calculation and tuning and its easy implementation and capability of constraints handling. In addition, PFC has many advantages over PID control. First, it can control time delay processes and constrain both the manipulated and controlled variables. Second, the tuning parameters have physical meaning, which is helpful for applying algorithms to practice. Therefore, if PID control and PFC are combined, better control performance can be achieved. In many papers, various design methods of PID controllers based on predictive functional control optimization are proposed. But these papers are focused on SISO systems and they do not cover MIMO systems.
Based on the principle of decoupling control, Kang Chung Hyok, a researcher at the Faculty of Metal Engineering, has proposed a new design method of PID controllers by PFC optimization for MIMO systems with time delay.
First, after decoupling, he divided the complex MIMO systems with time delay into independent subsystems. Then, he designed a PID controller based on PFC optimization after simplifying the subsystems into FOPDT models. The proposed controller not only inherits the advantages of PFC, but also has the same structure as a PID controller.
The simulation results show that the proposed controller has more improved control performance and better robustness than traditional PID controllers under the conditions of time delay and model/plant mismatches, and that the actuator’s life can be lengthened as the manipulated variable has no oscillating characteristics. In summary, the proposed controller can meet the requirements of complex industrial processes.
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Jo Feb 6, 2025
Today, the energy demand of mankind is growing with each passing day, and the need for construction and operational stability of all power plants including thermal power plants is increasing. Therefore, many non-destructive testing (NDT) methods have been developed and used in safety analysis of power plants worldwide. X-ray inspection, ultrasonic inspection and magnetic particle inspection are typical ones. But these methods do not provide a guarantee for the safety of structures since they are not suitable for regular full-scale inspection of various structures in the industrial sector due to their high cost of inspection, artificial magnetization process of objects to be tested, complex operating conditions and high time consumption.
Recently, metal magnetic memory (MMM) method is widely used in the world for its cost-effectiveness, easy operation, time saving and high sensitivity. In particular, MMM method has two advantages. First, fatigue failure occurring in stress concentration zones (SCZ) can be diagnosed and prevented. Second, the inspection device is effective for regular whole inspection of different structures like power plants for its simplicity and high inspection speed.
Based on the metal magnetic memory test principle and the data on the sensor type, Ryu Yong Chol, a researcher at the General Assay Office, has selected sensor material for weak magnetostatic field measurement and made an SCZ inspector.
First, he determined the optimum excitation method for highest sensitivity, the influences of various factors on the characteristics of the sensor and the method of measuring the leakage magnetic field. Then, he conducted a tensile test and inspection on different specimens to verify its reliability.
The results show that MMM device enables fast inspection of ferromagnetic structures and diagnostics and prevention of fatigue failure in SCZ, which is impossible with other non-destructive testing methods.
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Jo Feb 4, 2025
Nowadays NdFeB magnets are widely used in many applications such as electric two-wheelers, air conditioners, hybrid and electric cars, MRI scanners, wind generators, HDD, acoustic transducers, magnetic separators, etc. Thus, the global demand for NdFeB magnets is expected to continuously increase in the near future.
However, the supply of rare earth elements including neodymium, praseodymium and dysprosium for NdFeB magnets does not meet this growing demand, so rare earth elements are regarded as critical elements. Despite their criticality, less than 1% of rare earths are being recycled from end-of-life rare earth permanent magnets. Moreover, during the manufacturing process of NdFeB magnets, approximately 20~30% of rare earth alloy are lost and stockpiled as industrial waste. Therefore, development of an efficient recycling process for separation and recovery of rare earths from end-of-life products and magnet waste is an important issue.
Rare earth double sulfate precipitation is a traditional method for separation of rare earths from non-rare earths, which has advantages such as simple operation, low reagent cost, easy filtration of rare earth precipitates, high recovery of rare earths, etc. However, recovery of rare earths from NdFeB magnet waste by the rare earth double sulfate precipitation has not been reported.
Kim Sok Chol, a section head at the Faculty of Chemical Engineering, has succeeded in applying the rare earth double sulfate precipitation to the separation and recovery of rare earths from the solution obtained by leaching NdFeB magnet waste with sulfuric acid on a laboratory scale. He has also conducted a pilot plant test in order to investigate and optimize the various steps of the whole process for its application on an industrial scale.
The process includes leaching of NdFeB magnet waste by sulfuric acid, precipitation of rare earths in the form of double sulfate by sodium chloride, and conversion of rare earth double sulfates into hydroxides.
The yields of neodymium and dysprosium in the whole process were 92.3% and 90.8%, respectively. In the final rare earth hydroxides, the total rare earth oxides (TREO) content was 79.8%, where the contents of neodymium and dysprosium were 94.2% and 5.8%, respectively.
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Jo Feb 3, 2025
Selection of the optimal plan for maintaining the roadway affected by mining operations, when mining coal seams in weak rock formations with complex conditions of occurrence, has been studied a lot over the past decades, which has brought about many successes.
The optimal design of roadway maintenance plan requires a precise understanding of the mechanical properties of the surrounding rock mass, the interaction between the rock mass and the installed support system, and the stress distribution induced around the mining face and around the tunnel. Hence, researchers have been trying to solve the roadway maintenance problem by empirical methods such as mechanical, statistical and visual methods and numerical simulation analysis.
Empirical methods, where the complex mechanical interaction between rock mass and roof support is represented by simple equations, are supported by a large database, but they generally neglect the stress distribution generated by mining, the geological relationships of roof support management systems, and the interaction between the support system and the rock mass. On the other hand, numerical simulation analysis, which is dependent on the subjective experience of humans, cannot reflect well the nonlinear relationship between the factors affecting the stability of workings, and thus, it is not reliable for stability determination.
To solve this problem, researchers have used GA and ANN or their combination to establish nonlinear relationships, predict the displacement of the roadway influenced by the roadway depth, principal stress, drilling method, and rock load, and determine the displacement of the rock mass around roadway and the geological parameters for mining. This intelligent analysis method is very effective for its objectivity when evaluating the stability of roadways in a region of relatively regular coal seams. However, when the coal seams are in an irregular state and the roadway is strongly affected by mining operation, the nonlinear relationships between the factors should be taken into account for stability determination.
Pak Tae Song, a section head at the Faculty of Mining Engineering, has found the optimal maintenance scheme of roadways strongly affected by mining operation for nonlinear problems by combining ANN with high adaptive capacity and GA with strong adaptive optimization ability.
He applied a two-stage ANN-GA. First, he obtained the installation space and failure rate of the support from the combination of ANN and GA in the second stage. Then, he found the optimal roadway maintenance scheme from the combination of ANN and GA in the first stage.
After that, he compared the selected scheme with field observations. The results show that the scheme is effective in optimizing the maintenance system of workings, which is affected by the nonlinear relationship among mining geological parameters.
The ANN-GA method can be effectively applied to the study of the geo-mechanical behavior of rock mass affected by the uncertainty relations of qualitative and quantitative factors caused by mining operations.
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