• Progress in Medical Physics
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• v.27 no.3
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• pp.125-130
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• 2016

Dual energy computed tomography (DECT) is used to classify two materials and quantify the mass density of each material in the human body. An energy modulation filter based DECT could acquire two images, which are generated by the low- and high-energy photon spectra, in one scan, with one tube and detector. In the case of DECT using the energy modulation filter, the filter should perform the optimization process for the type of materials and thicknesses for generating two photon spectra. In this study, Geant4 Monte-Carlo simulation toolkit was used to execute the optimization process for determining the property of the energy modulation filter. In the process, various materials used for the energy modulation filter are copper (Cu, $8.96g/cm^3$), niobium (Nb, $8.57g/cm^3$), stannum (Sn, $7.31g/cm^3$), gold (Au, $19.32g/cm^3$), and lead (Pb, $11.34g/cm^3$). The thickness of the modulation filter varied from 0.1 mm to 1.0 mm. To evaluate the overlap region of the low- and high-energy spectrum, Geant4 Monte-Carlo simulation is used. The variation of the photon flux and the mean energy of photon spectrum that passes through the energy modulation filter are evaluated. In the primary photon spectrum of 80 kVp, the optimal modulation filter is a 0.1 mm lead filter that can acquire the same mean energy of 140 kVp photon spectrum. The lead filter of 0.1 mm based dual energy CBCT is required to increase the tube current 4.37 times than the original tube current owing to the 77.1% attenuation in the filter.

• Journal of the Korea Computer Graphics Society
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• v.23 no.3
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• pp.105-113
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• 2017

This paper presents a novel on-line trajectory optimization framework based on automatic time warping, which performs the time warping of a reference motion while optimizing character motion control. Unlike existing physics-based character animation methods where sampling times for a reference motion are uniform or fixed during optimization in general, our method considers the change of sampling times on top of the dynamics of character motion in the same optimization, which allows the character to effectively respond to external pushes with optimal time warping. In order to do so, we formulate an optimal control problem which takes into account both the full-body dynamics and the change of sampling time for a reference motion, and present a model predictive control framework that produces an optimal control policy for character motion and sampling time by repeatedly solving the problem for a fixed-span time window while shifting it along the time axis. Our experimental results show the robustness of our framework to external perturbations and the effectiveness on rhythmic motion synthesis in accordance with a given piece of background music.

• Advances in Energy Research
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• v.5 no.1
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• pp.31-55
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• 2017

In the present study, PV/T collector was modeled via analysis of governing equations and physics of the problem. Specifications of solar radiation were computed based on geographical characteristics of the location and the corresponding time. Temperature of the collector plate was calculated as a function of time using the energy equations and temperature behavior of the photovoltaic cell was incorporated in the model with the aid of curve fitting. Subsequently, operational range for reaching to maximal efficiency was studied using Genetic Algorithm (GA) technique. Optimization was performed by defining an objective function based on equivalent value of electrical and thermal energies. Optimal values for equipment components were determined. The optimal value of water flow rate was approximately 1 gallon per minute (gpm). The collector angle was around 50 degrees, respectively. By selecting the optimal values of parameters, efficiency of photovoltaic collector was improved about 17% at initial moments of collector operation. Efficiency increase was around 5% at steady condition. It was demonstrated that utilization of photovoltaic collector can improve efficiency of solar energy-based systems.

• Nuclear Engineering and Technology
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• v.55 no.7
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• pp.2621-2627
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• 2023

In Experimental Advanced Superconducting Tokamak (EAST) experiments, to achieve long pulse and high-power ICRH system operation, a new kind of ICRH antenna has been designed. One of the most critical factors in limiting the operation of long pulse and high power is the intense heat load in the front face of the ICRH antenna, especially the Faraday Screen (FS). Therefore, the cooling channels of FS need to be designed. According to thermal-hydraulic analysis, the FS tubes are divided into several groups to achieve more excellent water cooling capability. The number of series and parallel tubes in one group is chosen as six. This antenna went into service in the spring of 2021, and it is delightful that the temperature distribution of the FS tube is below 400 ℃ in 14.5 s and 1.8 MW ICRH system operation. However, the active water-cooling design was not carried out on the upper and lower plates of FS, which led to severe ablations on that region under long pulse and high power operation, and the temperature is up to 800. Therefore, the upper and lower side plates of the FS were designed with water cooling based on thermal-hydraulic analysis. During the 2022 winter experiments, the temperature of ICRH antenna FS was lower than 400 in the pulse of 200s and the power of 1 MW operation.

• The Journal of Korea Robotics Society
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• v.17 no.1
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• pp.58-67
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• 2022

In this paper, we propose an approach resolving inaccuracy of the low-cost redundant manipulator workspace with low encoder and low stiffness. When the manipulators are manufactured with low-cost encoders and low-cost links, the robots can run into workspace inaccuracy issues. Furthermore, trajectory generation based on conventional forward/inverse kinematics without taking into account inaccuracy issues will introduce the risk of end-effector fluctuations. Hence, we propose an optimization for the trajectory generation method based on the DDPG (Deep Deterministic Policy Gradient) algorithm for the low-cost redundant manipulators reaching the target position in Euclidean space. We designed the DDPG algorithm minimizing the distance along with the jacobian condition number. The training environment is selected with an error rate of randomly generated joint spaces in a simulator that implemented real-world physics, the test environment is a real robotic experiment and demonstrated our approach.

• Journal of Korea Multimedia Society
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• v.21 no.8
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• pp.969-981
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• 2018

Recent advances in machine learning approaches such as deep neural network and reinforcement learning offer significant performance improvements in generating detailed and varied motions in physically simulated virtual environments. The optimization methods are highly attractive because it allows for less understanding of underlying physics or mechanisms even for high-dimensional subtle control problems. In this paper, we propose an efficient learning method for stochastic policy represented as deep neural networks so that agent can generate various energetic motions adaptively to the changes of tasks and states without losing interactivity and robustness. This strategy could be realized by our novel trajectory search method motivated by the trust region policy optimization method. Our value-based trajectory smoothing technique finds stably learnable trajectories without consulting neural network responses directly. This policy is set as a trust region of the artificial neural network, so that it can learn the desired motion quickly.

• Journal of the Optical Society of Korea
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• v.19 no.6
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• pp.604-613
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• 2015

An unobstructed off-axis two-mirror system is presented in this paper. First a suitable initial configuration is established based on third-order aberration theory. In order to achieve a wide field of view (FOV) with high image quality , the diffractive mirror is adopted in the two-mirror system to increase the optimization freedom and the aberration relationship between diffractive phase coefficients and Zernike coefficients is derived. Furthermore, a complete comparison design example with a focal length of 1200 mm, F-number of 12, and FOV of 40° × 2° is given to verify the aberration correction ability of the diffractive mirror. The system average wavefront error is 0.007 λ (λ=0.6328 μm) developed from 0.061 λ when the system didn’t adopt the diffractive mirror. In this system the phase modulation function of the diffractive mirror is established as an even function of x, so we could obtain a symmetrical imaging quality about the tangential plane, and the symmetric aberration performance also brings considerable convenience to alignment and testing for the system.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.23 no.5
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• pp.535-541
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• 2010

In this paper, we have derived a continuum-based adjoint design sensitivity of general performance functionals with respect to Young' modulus and heat conduction coefficient for steady-state nonlinear thermoelastic problems. An adjoint equation for temperature and displacement fields is defined for the efficient computation of the coupled field design sensitivity. Through numerical examples, we investigated the mesh dependency of the topology optimization method in the thermoelastic problems. Also, comparing the dominant loading cases of thermal and mechanical ones, the loading dependency of topology design optimization in coupled multi-physics problems is investigated.

• Nuclear Engineering and Technology
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• v.53 no.7
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• pp.2377-2386
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• 2021

To model the atmospheric dispersion of radionuclides released from nuclear accident is very important for nuclear emergency. But the uncertainty of model parameters, such as source term and meteorological data, may significantly affect the prediction accuracy. Data assimilation (DA) is usually used to improve the model prediction with the measurements. The paper proposed a parameter bias transformation method combined with Lagrangian puff model to perform DA. The method uses the transformation of coordinates to approximate the effect of parameters bias. The uncertainty of four model parameters is considered in the paper: release rate, wind speed, wind direction and plume height. And particle swarm optimization is used for searching the optimal parameters. Twin experiment and Kincaid experiment are used to evaluate the performance of the proposed method. The results show that the proposed method can effectively increase the reliability of model prediction and estimate the parameters. It has the advantage of clear concept and simple calculation. It will be useful for improving the result of atmospheric dispersion model at the early stage of nuclear emergency.

• Journal of the Optical Society of Korea
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• v.20 no.1
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• pp.118-124
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• 2016

The shape and location of the cutoff shield in a projection-type headlight system were optimized by a ray-tracing technique. A shield based on a Petsval surface showed better cutoff characteristics than a flat or cylindrical shield, such as a sharp intensity gradient and less color separation at the cutoff line. Adjustment of the shield’s location between the reflector and the aspheric lens further improved its cutoff characteristics.