• Korean Journal of Optics and Photonics
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• v.30 no.5
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• pp.193-196
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• 2019

The design and control of thermal flow is important for the operation of high-power laser diodes (LDs). It is necessary to analyze and improve the thermal bottleneck near the active layer of an LD. As the error in prediction of the thermal resistance of an LD is large, typically due to the hyperbolic increase and saturation to linear increase of the thermal resistance as a function of thickness, it is helpful to use a simple, modified divergence model for the improvement and optimization of thermal resistance. The characteristics of LDs are described quite well, in that the values for simulated thermal resistance curves and the thermal cross section followed are almost the same as the values from the model function. Also, the thermal-cross-section curve obtained by differentiating the thermal resistance is good for identifying thermal bottlenecks intuitively, and is also fitted quite well by the model proposed for both a typical LD structure and an improved LD with thin capping and high thermal conductivity.

• Journal of The Korean Astronomical Society
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• v.34 no.4
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• pp.333-335
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• 2001

We study the properties of supernova (SN) driven interstellar turbulence with a numerical magnetohydrodynamic (MHD) model. Calculations were done using the RIEMANN framework for MHD, which is highly suited for astrophysical flows because it tracks shocks using a Riemann solver and ensures pressure positivity and a divergence-free magnetic field. We start our simulations with a uniform density threaded by a uniform magnetic field. A simplified radiative cooling curve and a constant heating rate are also included. In this radiatively-cooling magnetized medium, we explode SNe one at a time at randomly chosen positions with SN explosion rates equal to and 12 times higher than the Galactic value. The evolution of the system is basically determined by the input energy of SN explosions and the output energy of radiative cooling. We follow the simulations to the point where the total energy of the system, as well as thermal, kinetic, and magnetic energy individually, has reached a quasi-stationary value. From the numerical experiments, we find that: i) both thermal and dynamical processes are important in determining the phases of the interstellar medium, and ii) the power index n of the $B-p^n$ relation is consistent with observed values.

• Nuclear Engineering and Technology
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• v.34 no.1
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• pp.30-41
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• 2002

The neutron beam is fully characterized for the prompt gamma activation analysis facility at Hanaro in the Korea Atomic Energy Research Institute(KAERI). The facility uses thermal neutrons which are diffracted vertically from a horizontal beam port by a set of pyrolytic graphite(PG) crystals positioned at the Bragg angle of 45" Neutron spectra, neutron flux and Cd-ratio are determined for the three extraction modes of diffracted beam by means of the theoretical and experimental efforts. To obtain theoretical result, the reflectivity of pyrolytic graphite is calculated in the diffraction model for mosaic crystal and the angular divergence after diffraction by mosaic crystal is estimated from Monte Carlo simulation. The time-of-flight spectrometer and gold activation wire are used for measuring the neutron spectra. Both the calculated and measured spectra have proven that the unique feature of polychromatic beam obtained by PG crystals are useful for PGAA. The thermal neutron flux of 7.9$\times$107 n/cm$^2$s and the Cd-ratio of 266 for gold have been achieved at the sample position while the reactor operates at 24 MW The uniformity of beam flux is 12% in the central 1$\times$1 cm$^2$ area. Finally, the beam is briefly characterized by the effective velocity and temperature which are determined by measuring the prompt Y-ray spectra for thin and thick boron samples.ples.

• Nuclear Engineering and Technology
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• v.55 no.1
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• pp.310-323
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• 2023

The k-eigenvalue neutronics/thermal-hydraulics coupling calculation is a key issue for reactor design and analysis. Jacobian-free Newton-Krylov (JFNK) method, featured with super-linear convergence rate and high efficiency, has been attracting more and more attention to solve the multi-physics coupling problem. However, it may converge to the high-order eigenmode because of the multiple solutions nature of the k-eigenvalue form of multi-physics coupling issue. Based on our previous work, a modified JFNK with a line search method is proposed in this work, which can find the fundamental eigenmode together with thermal-hydraulics feedback in a wide range of initial values. In detail, the existing modified JFNK method is combined with the line search strategy, so that the intermediate iterative solution can avoid a sudden divergence and be adjusted into a convergence basin smoothly. Two simplified 2-D homogeneous reactor models, a PWR model, and an HTR model, are utilized to evaluate the performance of the newly proposed JFNK method. The results show that the performance of this proposed JFNK is more robust than the existing JFNK-based methods.

• Journal of the Korean earth science society
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• v.30 no.3
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• pp.294-304
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• 2009

A statistical prediction model for the typhoon intensity and track in the Northwestern Pacific area was developed based on the artificial neural network scheme. Specifically, this model is focused on the 5-day prediction after tropical cyclone genesis, and used the CLIPPER parameters (genesis location, intensity, and date), dynamic parameters (vertical wind shear between 200 and 850hPa, upper-level divergence, and lower-level relative vorticity), and thermal parameters (upper-level equivalent potential temperature, ENSO, 200-hPa air temperature, mid-level relative humidity). Based on the characteristics of predictors, a total of seven artificial neural network models were developed. The best one was the case that combined the CLIPPER parameters and thermal parameters. This case showed higher predictability during the summer season than the winter season, and the forecast error also depended on the location: The intensity error rate increases when the genesis location moves to Southeastern area and the track error increases when it moves to Northwestern area. Comparing the predictability with the multiple linear regression model, the artificial neural network model showed better performance.