• Journal of Biomedical Engineering Research
• /
• v.32 no.1
• /
• pp.15-24
• /
• 2011

While Compton imaging is recognized as a valuable 3-D technique in nuclear medicine, reconstructing an image from Compton scattered data has been of a difficult problem due to its computational complexity. The most complex and time-consuming computation in Compton camera reconstruction is to perform the conical projection and backprojection operations. To alleviate the computational burden imposed by these operations, we investigate a rebinning method which can convert conical projections into parallel projections. The use of parallel projections allows to directly apply the existing deterministic reconstruction methods, which have been useful for conventional emission tomography, to Compton camera reconstruction. To convert conical projections into parallel projections, a cone surface is sampled with a number of lines. Each line is projected onto an imaginary plane that is mostly perpendicular to the line. The projection data rebinned in each imaginary plane can then be treated as the standard parallel projection data. To validate the rebinning method, we tested with the representative deterministic algorithms, such as the filtered backprojection method and the algebraic reconstruction technique. Our experimental results indicate that the rebinning method can be useful when the direct application of existing deterministic methods is needed for Compton camera reconstruction.

• Journal of Korean Society of Occupational and Environmental Hygiene
• /
• v.19 no.4
• /
• pp.328-334
• /
• 2009

There are various methods for welding fume control. These methods can be divided into local exhaust system, general ventilation system and integrated control system. With the general ventilation system, we should have a good prediction tool for testing various appropriate control options. But, until now there are not many studies about how to predict the welding fume concentrations. Especially, the prediction of welding fume concentration is not a very easy task because welding fume is the particulate matters. In this study, we tried to measure $CO_2$ concentrations and welding fume concentrations in a small single room with a small ventilation opening. Using commercially available CFD (Computational Fluid Dynamics) software, we tried to predict $CO_2$ concentrations under the exactly same conditions. Then, we tried to compare the numerical $CO_2concentrations$ with the experimental results to know whether we could predict $CO_2$ concentrations. Then we tried to compare $CO_2$ concentrations with experimental welding fume concentrations to know whether we can use the numerical $CO_2concentrations$ to predict the welding fume concentration indirectly.

• Membrane and Water Treatment
• /
• v.8 no.5
• /
• pp.423-435
• /
• 2017

Settling Basins are one of the most important and popular methods for removal of suspended sediments irrigation and drainage networks or power canals taking off from an alluvial river and wastewater treatment plant. Improving the performance and so increasing sediment removal efficiency of settling basins by an alternative method is necessary. In the present work, the effect of baffle and its angle of attack with the flow (${\theta}$) on the sediment removal efficiency is investigated by conducting a series of experiments on a straight canal with 8 m length, 0.3 m width and 0.5 m height and 3 m length of basin equipped with an adjustable glass baffle. A numerical analysis has been carried out using ANSYS Fluent 3D software (a general purpose computational fluid dynamics simulation tool) for three Froude numbers from the experiments. The numerical and experimental results were found to match reasonably well.

• Journal of Aerospace System Engineering
• /
• v.18 no.2
• /
• pp.40-46
• /
• 2024

This study suggests a method to enhance drone flight path planning and safety evaluation in urban areas using Computational Fluid Dynamics (CFD). As the use of drones in urban environments has been growing rapidly, there is a lack of established methods for path planning and safety evaluation, which leads to a risky approach relying on experimental methods. Therefore, this research takes into account the intricate 3D fluid dynamics between drones and buildings by employing CFD to quantitatively plan flight paths and evaluate their safety. To accomplish this, the study focuses on Gimcheon Innovation City as the target area and collects relevant terrain and building data, and selects prospective flight routes. CFD analysis is then carried out to gather essential data for flight simulations and safety assessment. The safety assessments are conducted based on environmental fluid dynamics when the drone operates along the proposed flight paths

• Journal of Korea Multimedia Society
• /
• v.19 no.3
• /
• pp.531-538
• /
• 2016

In this paper, we propose a novel post-processing method of semantic segmentation from indoor scenes with RGBD inputs. For accurate segmentation, various post-processing methods such as superpixel from color edges or Conditional Random Field (CRF) method considering neighborhood connectivity have been used, but these methods are not efficient due to high complexity and computational cost. To solve this problem, we maximize the efficiency of post processing by using depth superpixel extracted from disparity image to handle object silhouette. Our experimental results show reasonable performances compared to previous methods in the post processing of semantic segmentation.

• 한국전산유체공학회:학술대회논문집
• /
• 2006.10a
• /
• pp.131-135
• /
• 2006

The aerodynamic characteristics of a T-50 aircraft configuration are investigated by a subsonic panel method. Panel methods are best applicable to the lifting surfaces such as wings and airfoils. Source and doublets are used in the present code as a basic singularities of the panel technique. The panel method is first assessed by applying it to several benchmark problems for which other solutions and experimental data are available, such as a swept wing and wing body configuration. The prediction results are compared with experimental data and show good agreement in all cases considered. Finally, the method is applied to a T-50 aircraft configuration and excellent agreement with flight test data in lift coefficients is found.

• Journal of Mechanical Science and Technology
• /
• v.15 no.5
• /
• pp.569-579
• /
• 2001

This study investigates the effects of operating conditions on the chattering of an automotive disk brake by experimental and computational methods. Design factors, which cause chattering in automobiles, have attracted great attentions for long time; but they are not well understood yet. For this study, we construct a brake dynamometer for measuring the disk surface temperature during chattering, and propose an efficient hybrid algorithm (combining FFT-FEA and traditional FEA program) for analyzing the thermo-elastic behavior of three-dimensional brake system. We successfully measure the judder in a brake system via the dynamometer and efficiently simulate the contact pressure variation by the hybrid algorithm. The three-dimensional simulation of thermo-mechanical interactions on the automotive brake, showing the transient thermo-elastic instability phenomenon, is presented for the first time in this academic community. We also find from the experimental study that the disk bulk temperature strongly influences the brake chattering in the automotive disk brakes.

• Structural Engineering and Mechanics
• /
• v.25 no.1
• /
• pp.75-89
• /
• 2007

Post-earthquake reconnaissance and experimental research indicate that squat reinforced concrete (RC) columns in existing buildings or bridge piers are vulnerable to non-ductile shear failure. Recently, several experimental studies were conducted to investigate upgrading the shear resistance capacity of such columns in order to modify their failure mode to ductile one. Among these upgrading methods is the use of fibre-reinforced polymer (FRP) jackets. One of the preferred analytical tools to simulate the response of frame structures to earthquake loading is the lumped plasticity macromodels due to their computational efficiency and reasonable accuracy. In these models, the columns' nonlinear response is lumped at its ends. The most important input data for such type of models is the element's lateral force-displacement backbone curve. The objective of this study is to verify an analytical method to predict the lateral force-displacement ductility relationship of axially and laterally loaded rectangular RC squat columns retrofitted with FRP composites. The predicted relationship showed good accuracy when compared with tests available in the literature.

• Journal of the Computational Structural Engineering Institute of Korea
• /
• v.30 no.1
• /
• pp.87-94
• /
• 2017

Reliability analysis(RA) and Reliability-based design optimization(RBDO) require statistical modeling of input random variables, which is parametrically or nonparametrically determined based on experimental data. For the parametric method, goodness-of-fit (GOF) test and model selection method are widely used, and a sequential statistical modeling method combining the merits of the two methods has been recently proposed. Kernel density estimation(KDE) is often used as a nonparametric method, and it well describes a distribution function when the number of data is small or a density function has multimodal distribution. Although accurate statistical models are needed to obtain accurate RA and RBDO results, accurate statistical modeling is difficult when the number of data is small. In this study, the accuracy of two statistical modeling methods, SSM and KDE, were compared according to the number of data. Through numerical examples, the RA results using the input models modeled by two methods were compared, and appropriate modeling method was proposed according to the number of data.

• Proceedings of the KSME Conference
• /
• 2008.11a
• /
• pp.1169-1175
• /
• 2008

The validation technique is classified with two methods whether to demand of additional experimental points. The method which requires additional experimental points such as RSME is actually impossible in engineering field. Therefore, the method which only use experimented points such as the cross validation technique is only available. But the cross validation not only requires considerable computational costs for generating metamodel each iterations, but also cannot measure quantitatively the fidelity of metamodel. In this research we propose a new validation technique for representative metamodels using an variance of metamodel and confidence interval information. The proposed validation technique computes confidence intervals using a variance information from the metamodel. This technique will have influence on choosing the accurate metamodel, constructing ensemble of each metamodels and advancing effectively sequential sampling technique.