Jo Nov 30, 2023
Rotating machinery, which plays an important role in modern industries, is in extensive range of mechanical applications such as steam and gas turbines, air craft and automobile engines, pumps and even domestic applications. In the rotating machinery shaft one of the most serious damages is crack, and catastrophic failures and dangerous accidents may occur from cracks in aircraft engines and other rotating machinery. A very rich amount of literature about cracked rotors has appeared in the last four decades.
A lot of researches were conducted on cracked general shafts, but few studies of the modeling of hollow shafts with cracks were found. Most studies used classical models in modeling the crack breathing in hollow shafts.
Yang Hyong Ju, a researcher at the Faculty of Mechanical Science and Technology, has studied the actual breathing mechanism of a hollow shaft and presented generalized breathing functions of cracks. On the basis of it, he formulated an exact time-varying stiffness matrix of cracked elements and derived a finite element model of a rotor system. Then, he employed HBM to find the response, orbits and critical and subcritical speeds of a cracked rotor system. Finally, he analyzed the nonlinear vibration of a rotor system and compared the results with some published results, considering the eccentricity of disk, dimensionless crack depth, ratio of the inner radius to the outer radius of the rotor and angle between the crack and imbalance directions.
The results showed that the proposed generalized functions are more accurate than classical models, and they are superior to the functions introduced in previous studies in terms of generality.
If further information is needed, you can refer to his paper “Generalized breathing functions for stiffness model of transversely cracked hollow shaft” in “International Journal of Structural Stability and Dynamics” (SCI).
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Jo Nov 29, 2023
The most important open problem of the studies of quantum mechanics is to elucidate why probability density is the modulus square of a wave function.
This problem has been a fundamental subject of a long-standing debate that began soon after quantum theory was basically formulated in 1920s.
Within the framework of the standard theory of quantum mechanics, the relation between wave function and probability density is assumed rather than derived.
Successful works which aim to elucidate this assumption theoretically are not yet known.
This problem is related to in what space quantum mechanics should be constructed.
For the purpose of solving this problem, Jong Chol, a researcher at the Faculty of Materials Science and Technology, has deduced a fundamental equation of quantum mechanics by starting with probability density.
To do so, it was necessary for him to formulate a new theory of quantum mechanics distinguished from the previous ones. His investigation shows that it is possible to construct quantum mechanics in phase space as an alternative autonomous formulation and such possibility enables us to study quantum mechanics by starting with probability density rather than wave function.
This direction of research is contrary to configuration-space formulation of quantum mechanics starting with wave function.
The work leads to a full understanding of the wave function as mathematically and physically sufficient representation of quantum-mechanical state which supplements information on quantum state given solely by probability density with phase information on quantum state.
The final result of the work is that quantum mechanics in phase space satisfactorily elucidates the relation between wave function and probability density by using the consistent procedure starting with probability density, thus withdrawing a main assumption of quantum mechanics.
You can find more information about this in his paper “Explanation of Relation between Wave Function and Probability Density Based on Quantum Mechanics in Phase Space” in “World Journal of Mechanics”.
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Jo Nov 28, 2023
Mining Method Selection (MMS) is the first and the most critical problem in mine design, and it depends on some parameters such as geometric and geological features and economic factors.
The ultimate goals of mining method selection are maximizing profit, enhancing mining recovery rate and providing a safe mining environment.
Selection of an appropriate mining method is a complex task that requires consideration of many technical, economic, social, and historical factors.
Pak Myong Chun, a section head at the Faculty of Mining Engineering, determined the factors affecting MMS with the help of some mining experts, and selected the most suitable mining method using the hesitant fuzzy group decision-making (HFGDM) and technique for order performance by similarity to the ideal solution (TOPSIS). These factors included type of deposit, slope of deposit, thickness of orebody, depth below the surface, grade distribution, hanging wall Rock Mass Rating (RMR), footwall RMR, ore body RMR, recovery, capital cost, mining cost, annual productivity, and environmental impact.
Firstly, he proposed a group decision-making (GDM) method to determine the weights of several attributes based on the score function with decision-makers’ weights, in which the n-dimensional hesitant fuzzy environment takes the form of hesitant fuzzy sets (HFS). Then, he calculated the weights of these factors using the HFGDM method. He compared seven mining methods for an apatite mine to select the optimal mining method using the TOPSIS method.
The results showed that the sub-level stoping method with priority of 0.811 3 was the best for the studied mine.
For more information, please refer to his paper “Suitable Mining Method Selection using HFGDM-TOPSIS Method: a Case Study of an Apatite Mine” in “Journal of Mining and Environment” (EI).
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Jo Nov 25, 2023
Generally, least squares (LS) method treats only random errors of observation vector in adjustment function models. However, both observation vector and elements of coefficient matrix of an adjustment function model contain random errors. Therefore, the adjustment result of least square method does not guarantee a global-optimal solution.
Since total least square (TLS) method takes into account both random errors of observation vector and coefficient matrix based on an errors-in-variables (EIV) model, it is possible to improve the accuracy more than the result by LS method. TLS method has been further systematically developed and widely applied to many science and engineering problems, namely some practical problems, such as those in signal processing, statistical calculation and regression analysis.
Kim Jung Hyang, a researcher at the Faculty of Earth Science and Technology, has described a parameter adjustment method based on Weighted Total Least Square (WTLS) method and verified effectiveness of this method through application in simulated network. He has shown its advantage in comparison with classical LS and TLS methods.
The results show that the WTLS method based on an EIV model can further improve the accuracy of adjustment results as it handles simultaneously all kinds of random errors involved in the observation system.
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Jo Nov 24, 2023
In the environmental protection and petroleum industries, advanced technologies for separating water and oil are essential. Selective separation of oil and water is an important means of oil and water separation, and superoleophilic and superoleophobic properties of microstructure surface in water have attracted attentions of many researchers. Contact angle is greatly affected by interactions between the liquid and the solid and by chemical characteristics and roughness of a solid surface. For a certain solid surface, surface roughness is a key factor in controlling contact angle.
Contact angle is usually used for study of wetting phenomenon while wetting equations connect experimental measurement variables and wetting phenomenon. Wettability phenomenon can be theoretically explained by wettability equation.
Previous numerical simulations on static contact angle and dynamic contact angle of droplets on surfaces were mainly directed to water droplets in the air. Two-dimensional numerical simulations were used to study static and dynamic properties of water droplets in the air. Numerical simulations on static contact angles and dynamic contact angles of oil droplets in water were rarely found.
Choe Hyon Chol, a researcher at the Faculty of Mechanical Science and Technology, has conducted a 3-dimensional numerical simulation on the underwater apparent contact angle of oil droplets on the microstructure-textured surface by VOF method.
The results are as follows.
The height of a microstructure layer on the surface is an important variable that affects the wettability of a solid surface. When the surface of material is oleophobic in water, an increased microstructure height increases roughness factor, apparent contact angle of an oil droplet and oleophobic nature of surface. When the surface of material is oleophilic in water, an increased microstructure height reduces apparent contact angle and makes the surface more oleophilic.
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Jo Nov 22, 2023
Incomplete data are a common problem arising in data analysis. There are many methods to treat incomplete data including deletion and imputation.
However, they may be unsuitable in case of relatively large amount of missing values.
Yang Won Chol, a researcher at the Faculty of Materials Science and Technology, has proposed a method to develop a multiple regression model with block missed incomplete data.
The outline of the method is as follows: (a) separate submatrices from block missed incomplete data, (b) develop multiple regression submodels from the submatrices, and (c) develop a final multiple regression model by linear or nonlinear combination of the submodels.
By applying the proposed method, he conducted a simulation experiment on three datasets and developed a prediction model of casting density for A380 according to die casting process parameters.
The results demonstrated that the performance and data usage rate of the proposed method is far superior to the previous methods.
First, the proposed method to develop a multiple regression model with block missed incomplete data ensures a high performance, statistical stability and reliability of the final multiple regression model, and ensures data usage rate of 100%.
Second, the final multiple quadratic regression model by quadratic combination of regression submodels has better performance than the final multiple linear regression model by linear combination of regression submodels.
Third, when some features of a new object are not observed, it is possible to predict the target value by using final regression submodels.
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