• Bulletin of the Korean Chemical Society
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• v.16 no.11
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• pp.1084-1088
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• 1995

A complete solid solution (SrLaAl1-xNixO4) between insulating SrLaAlO4 and metallic SrLaNi(Ⅲ)O4 oxides were prepared under high oxygen pressure (1.5 kbar, 800 ℃). They have tetragonal K2NiF4-type structure in all the solid solution range. Compared with lattice parameters of the same solid solution prepared under normal condition (1 bar, 1200 ℃), large decrease in the c-parameter was induced by high pressure treatment while no noticeable variation of the a-parameter was observed. Although marked changes of structural parameters, magnetic susceptibilities, and electron paramagnetic resonance spectra were consistently occurred before and after x=0.5, overall behaviors were essentially the same with those of solid solution prepared under normal condition. Such a phenomenon is explained by assuming the formation of partially filled narrow σ*x2-y2 band for x>0.5. Lattice contraction along the c-axis by high pressure treatment seems not to broaden this band. Particularly, the continuous absorption characteristic of a high free carrier concentration for x>0.5 and the absence of Ni-O in-plane stretching mode in the infrared absorption spectra supports this picture. However, the conductivities increasing with temperature for all solid solution suggest that some localization character, of probably Anderson type, remains for x>0.5.

• Journal of Korean Society for Quality Management
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• v.47 no.1
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• pp.87-96
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• 2019

Purpose: The purpose of this paper is to determine an optimal production time for economic production quantity model with preventive maintenance and random defective rate as the function of a machinery deteriorates. Methods: If a machinery shifts from "in-control" state to "out-of-control" state, a proportion of defective items being produced increases. It is assumed that time to state shift is a random variable and follows an arbitrary distribution. The elapsed time until process shift decreases stochastically as a production cycle repeats and quasi-renewal process is used to implement for production facilities to deteriorate. Results: When the exponential parameter for exponential distribution increases, the optimal production time increases. When Weibull distribution is considered, the optimal production time is closely affected by the shape parameter of Weibull distribution. Conclusion: A mathematical model is suggested to find optimal production time and optimal number of production cycles and numerical examples are implemented to validate the patterns for changes of optimal times under different parameters assumptions. The real application is implemented using the proposed approach.

• Nuclear Engineering and Technology
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• v.50 no.7
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• pp.1017-1023
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• 2018

The measurement and calculation of neutronic parameters in nuclear research reactors has an important influence on control and safety of the nuclear reactor. The power peaking factors, reactivity coefficients and kinetic parameters are the most important neutronic parameter for determining the state of the reactor. The position of the control shim safety rods in the core configuration affects these parameters. The main purpose of this work is to use the MTR_PC package to evaluate the effect of the partially insertion of the control rod on the neutronic parameters at the operating core of the Tehran Research Reactor. The simulation results show that by increasing the insertion of control rods (bank) in the core, the absolute values of power peaking factor, reactivity coefficients and effective delayed neutron fraction increased and only prompt neutron life time decreased. In addition, the results show that the changes of moderator temperature coefficients value versus the control rods positions are very significant. The average value of moderator temperature coefficients increase about 98% in the range of 0-70% insertion of control rods.

• Nuclear Engineering and Technology
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• v.53 no.4
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• pp.1199-1209
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• 2021

The detection of unexpected loose parts in the primary coolant system in a nuclear power plant remains an extremely important issue. It is essential to develop a methodology for the localization and mass estimation of loose parts owing to the high prediction error of conventional methods. An effective approach is presented for the localization and mass estimation of a loose part using machine-learning and deep-learning algorithms. First, a methodology was developed to estimate both the impact location and the mass of a loose part at the same times in a real structure in which geometric changes exist. Second, an impact database was constructed through a series of impact finite-element analyses (FEAs). Then, impact parameter prediction modes were generated for localization and mass estimation of a simulated metallic loose part using machine-learning algorithms (artificial neural network, Gaussian process, and support vector machine) and a deep-learning algorithm (convolutional neural network). The usefulness of the methodology was validated through blind tests, and the noise effect of the training data was also investigated. The high performance obtained in this study shows that the proposed methodology using an FEA-based database and deep learning is useful for localization and mass estimation of loose parts on site.

• Journal of applied mathematics & informatics
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• v.39 no.3_4
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• pp.419-435
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• 2021

This paper deals with numerical treatment of singularly perturbed differential equations involving small delays. The highest order derivative in the equation is multiplied by a perturbation parameter 𝜀 taking arbitrary values in the interval (0, 1]. For small 𝜀, the problem involves a boundary layer of width O(𝜀), where the solution changes by a finite value, while its derivative grows unboundedly as 𝜀 tends to zero. The considered problem contains delay on the convection and reaction terms. The terms with the delays are approximated using Taylor series approximations resulting to asymptotically equivalent singularly perturbed BVPs. Inducing exponential fitting factor for the term containing the singular perturbation parameter and using central finite difference for the derivative terms, numerical scheme is developed. The stability and uniform convergence of difference schemes are studied. Using a priori estimates we show the convergence of the scheme in maximum norm. The scheme converges with second order of convergence for the case 𝜀 = O(N^-1) and for the case 𝜀 ≪ N^-1, the scheme converge uniformly with first order of convergence, where N is number of mesh intervals in the domain discretization. We compare the accuracy of the developed scheme with the results in the literature. It is found that the proposed scheme gives accurate result than the one in the literatures.

• Current Optics and Photonics
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• v.4 no.6
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• pp.500-508
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• 2020

The rifling angle of artillery is an important parameter, and its determination plays a key role in the stability, hit rate, accuracy and service life of artillery. In this study, we propose an optical measurement method for the rifling angle based on angle error correction. The method is based on the principle of geometrical optics imaging, where the rifling on the inner wall of the artillery barrel is imaged on a CCD camera target surface by an optical system. When the measurement system moves in the barrel, the rifling image rotates accordingly. According to the relationship between the rotation angle of the rifling image and the travel distance of the measurement system, different types of rifling equations are established. Solving equations of the rifling angle are deduced according to the definition of the rifling angle. Furthermore, we added an angle error correction function to the method that is based on the theory of dynamic optics. This function can measure and correct the angle error caused by the posture change of the measurement system. Thus, the rifling angle measurement accuracy is effectively improved. Finally, we simulated and analyzed the influence of parameter changes of the measurement system on rifling angle measurement accuracy. The simulation results show that the rifling angle measurement method has high measurement accuracy, and the method can be applied to different types of rifling angle measurements. The method provides the theoretical basis for the development of a high-precision rifling measurement system in the future.

• Wind and Structures
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• v.34 no.1
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• pp.137-149
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• 2022

In this paper, the fluctuating lift and drag forces on 5:1 rectangular cylinders with two different geometric scales in three turbulent flow-fields are investigated. The study is particularly focused on understanding the influence of the ratio of turbulence integral length scale to structure characteristic dimension (the length scale ratio). The results show that both fluctuating lift and drag forces are influenced by the length scale ratio. For the model with the larger length scale ratio, the corresponding fluctuating force coefficient is larger, while the spanwise correlation is weaker. However, the degree of influence of the length scale ratio on the two fluctuating forces are different. Compared to the fluctuating drag, the fluctuating lift is more sensitive to the variation of the length scale ratio. It is also found through spectral analysis that for the fluctuating lift, the change of length scale ratio mainly leads to the variation in the low frequency part of the loading, while the fluctuating drag generally follows the quasi-steady theory in the low frequency, and the slope of the drag spectrum at high frequencies changes with the length scale ratio. Then based on the experimental data, two empirical formulas considering the influence of length scale ratio are proposed for determining the lift and drag aerodynamic admittances of a 5:1 rectangular cylinder. Furthermore, a simple relationship is established to correlate the turbulence parameter with the fluctuating force coefficient, which could be used to predict the fluctuating force on a 5:1 rectangular cylinder under different parameter conditions.

• Advances in materials Research
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• v.11 no.1
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• pp.1-22
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• 2022

In this paper, the nonlocal integral Timoshenko beam model is employed to study the free vibration characteristics of singled walled carbon nanotubes (SWCNTs) including the thermal effect. Based on the nonlocal continuum theory, the governing equations of motion are formulated by considering thermal effect. The influences of small scale parameter, the chirality of SWCNTs, the vibrational mode number, the aspect ratio of SWCNTs and temperature changes on the thermal vibration properties of single-walled nanotubes are examined and discussed. Results indicate significant dependence of natural frequencies on the nonlocal parameter, the temperature change, the aspect ratio and the chirality of SWCNTs. This work should be useful reference for the application and the design of nanoelectronics and nanoelectromechanical devices that make use of the thermal vibration properties of SWCNTs.

• Journal of Biosystems Engineering
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• v.37 no.4
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• pp.271-278
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• 2012

Worldwide trends in animal welfare have resulted in an increased interest in individual management of sows housed in groups within hog barns. Estrus detection has been shown to be one of the greatest determinants of sow productivity. Purpose: We conducted this study to develop a method that can automatically detect the estrus state of a sow by selecting optimal texture parameters from images of a sow's pudendum and by optimizing the number of neurons in the hidden layer of an artificial neural network. Methods: Texture parameters were analyzed according to changes in a sow's pudendum in estrus such as mucus secretion and expansion. Of the texture parameters, eight gray level co-occurrence matrix (GLCM) parameters were used for image analysis. The image states were classified into ten grades for each GLCM parameter, and an artificial neural network was formed using the values for each grade as inputs to discriminate the estrus state of sows. The number of hidden layer neurons in the artificial neural network is an important parameter in neural network design. Therefore, we determined the optimal number of hidden layer units using a trial and error method while increasing the number of neurons. Results: Fifteen hidden layers were determined to be optimal for use in the artificial neural network designed in this study. Thirty images of 10 sows were used for learning, and then 30 different images of 10 sows were used for verification. Conclusions: For learning, the back propagation neural network (BPN) algorithm was used to successful estimate six texture parameters (homogeneity, angular second moment, energy, maximum probability, entropy, and GLCM correlation). Based on the verification results, homogeneity was determined to be the most important texture parameter, and resulted in an estrus detection rate of 70%.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.307-311
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• 2003

2-mass system is generally used as controller of the variable-speed to transfer electromotion power to mechanical load such as industrial robot, driving parts of electric vehicle, rolling machine system of steel plant and driving parts of elevator. In this case, PI controller is often used as a velocity controller because of simplicity of system. But PI control algorithm is not enough for obtaining the control characteristics required for this system. To solve this problem, 2-mass system based on the PID controller derives the optimum PID parameters by pole assignment and estimation of the ITAE performance index. In this case, the system have tenacious properties about disturbance, but it causes extreme overshoot and vibration because of rapidly output of controller in early transient response about desired value. And if speed control system is applied by 2-DOF parameter ${\alpha}$, a temporary value, we must induce most suitable parameter by complicate pole assignment and estimation of the ITAE performance index whenever ${\alpha}$ changes. In this paper, to solve this problem we suggest control algorithm to followed exactly value of ${\alpha}$ as 2-DOF parameter by using fuzzy algorithm . So, intelligence algorithm modeled by human knowledge, experience, teachability and judgment follow exact ${\alpha}$ value and it can compose the efficient 2-DOF PID controller to improve following performance, overshoot decrease.