• 한국연소학회:학술대회논문집
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• 2004.06a
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• pp.133-137
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• 2004

The present study is focused on the small scale turbulent mixing processes in the scalar field. In order to deal with molecular mixing in turbulent flow, the linear eddy model is addressed. In each realization, the molecular mixing term is implemented deterministically, and turbulent stirring is represented by a sequence of instantaneous, statistically independent rearrangement event called by triplet map. The LEM approach is applied with relatively simple conditions. The characteristics of scalar mixing and PDF profiles are addressed in detail.

• 한국연소학회:학술대회논문집
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• 2012.11a
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• pp.61-62
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• 2012

The present study has numerically investigated the effects of fuel-side dilution and pressure on flame structure and extinction scalar dissipation rate of turbulent syngas nonpremixedd flames. Numerical results indicate that for highly diluted case, peak temperature is decreased and stoichiometric mixture fraction is increased. By decreasing the pressure and the nitrgen dilution levelcreased, the extinction scalar dissipation rate is increased.

• 한국연소학회:학술대회논문집
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• 2003.12a
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• pp.57-61
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• 2003

In the combustion modeling of non-premixed flames, the mixture fraction conserved scalar approach is widely utilized because reactants are mixed at the molecular level before burning and atomic elements are conserved in chemical reactions. In the mixture fraction approach, combustion process is simplified to a mixing problem and the interaction between chemistry and turbulence could be modelled by many sophisticated combustion models including the flamelet model and CMC. However, most of the mixture fraction approach is restricted to one mixture system. In this study, the flamelet model based on the two-feed system is extended to the multiple fuel-feeding systems by the two mixture fraction conserved scalar approach.

• Proceedings of the Korean Information Science Society Conference
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• 2002.10c
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• pp.682-684
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• 2002

최근 여러 논문에서 실 데이터 종속을 제거하기 위하여 결과 값 예상 기법을 제안하였다. 결과 값 예상 기법 중 혼합형 결과 값 예측기는 다양한 패턴을 갖는 명령어를 모두 예측함으로써 높은 예상 정확도를 얻을 수 있지만 하나의 명령어가 여러 개의 예측기 테이블에 중복 저장되어 높은 하드웨어 비용을 요구한다는 단점이 있다. 본 논문에서는 이러한 단점을 극복하기 위하여 프로파일링으로 얻어진 정적 분류 정보를 사용하여, 명령어률 예상 정확도가 높은 예측기에만 할당하여 예상 테이블 크기를 감소 시켰다. 또한 동적으로 적절한 예측기를 선택하도록 함으로써 예상 정확도를 더욱 향상 시켰다. 본 논문에서는 SPECint95 벤치마크 프로그램에 대해 SimpleScalar/PISA 3.0 툴셋을 사용하여 실험하였다. 정적-동적 분류 정보를 모두 사용하였을 경우 87.9%, VHT 크기를 4K로 축소한 경우 87.5%로 비슷한 예상정확도를 얻으면서 예상 테이블의 크기는 50%로 감소하였다. 또한 실행 패턴의 유형 비율에 따라 각 예측기의 VHT를 구성한 경우 예상 테이블 크기를 25%로 줄일 수 있었다.

• Journal of KIISE:Computer Systems and Theory
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• v.30 no.10
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• pp.569-578
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• 2003

Data dependencies are one of major hurdles to limit ILP(Instruction Level Parallelism), so several related works have suggested that the limit imposed by data dependencies can be overcome to some extent with use of the data value prediction. Hybrid value predictor can obtain the high prediction accuracy using advantages of various predictors, but it has a defect that same instruction has overlapping entries in all predictor. In this paper, we propose a new hybrid value predictor which achieves high performance by using the information of static and dynamic classification. The proposed predictor can enhance the prediction accuracy and efficiently decrease the prediction table size of predictor, because it allocates each instruction into single best-suited predictor during the fetch stage by using the information of static classification. Also, it can enhance the prediction accuracy because it selects a best- suited prediction method for the “Unknown”pattern instructions by using the dynamic classification mechanism. Simulation results based on the SimpleScalar/PISA tool set and the SPECint95 benchmarks show the average correct prediction rate of 85.1% by using the static classification mechanism. Also, we achieve the average correction prediction rate of 87.6% by using static and dynamic classification mechanism.

• Korean Journal of Agricultural and Forest Meteorology
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• v.17 no.3
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• pp.227-235
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• 2015

Using eddy covariance method, net ecosystem exchange (NEE) of $CO_2$ ($F_{CO_2}$), $H_2O$ (LE), and sensible heat (H) can be approximated as the sum of eddy flux ($F_c$) and storage flux term ($F_s$). Depending on strength and distribution of sink/source of scalars and magnitude of vertical turbulence mixing, the rates of changes in scalars are different with height. In order to calculate $F_s$ accurately, the differences should be considered using scalar profile measurement. However, most of flux sites for agricultural lands in Asia do not operate profile system and estimate $F_s$ using single-level scalars from eddy covariance system under the assumption that the rates of changes in scalars are constant regardless of the height. In this study, we measured $F_c$ and $F_s$ of $CO_2$, $H_2O$, and air temperature ($T_a$) using eddy covariance and profile system (i.e., the multi-level measurement system in scalars from eddy covariance measurement height to the land surface) at the Chengmicheon farmland site in Korea (CFK) in order to quantify the differences between $F_s$ calculated by single-level measurements ($F_s_{-single}$ i.e., $F_s$ from scalars measured by profile system only at eddy covariance system measurement height) and $F_s$ calculated by profile measurements and verify the errors of NEE caused by $F_s_{-single}$. The rate of change in $CO_2$, $H_2O$, and Ta were varied with height depending on the magnitudes and distribution of sink and source and the stability in the atmospheric boundary layer. Thus, $F_s_{-single}$ underestimated or overestimated $F_s$ (especially 21% underestimation in $F_s$ of $CO_2$ around sunrise and sunset (0430-0800 h and 1630-2000 h)). For $F_{CO_2}$, the errors in $F_s_{-single}$ generated 3% and 2% underestimation of $F_{CO_2}$ during nighttime (2030-0400 h) and around sunrise and sunset, respectively. In the process of nighttime correction and partitioning of $F_{CO_2}$, these differences would cause an underestimation in carbon balance at the rice paddy. In contrast, there were little differences at the errors in LE and H caused by the error in $F_s_{-single}$, irrespective of time.

• Journal of computational fluids engineering
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• v.11 no.4 s.35
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• pp.67-74
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• 2006

The characteristics of turbulent flow and mixing in a small can type combustor are investigated by means of Large Eddy Simulation (LES). Attention is paid for a combustor having a baffle plate with oxidant injection and fuel injection holes and study is made for three cases of different baffle plate configurations. From the result, it is confirmed that mixing is promoted by interaction between the jets during their developing process and large vortical flows generated in the vicinity of the combustor wall or fuel jet front. This particular flow feature is effective to accelerate the slow mixing between fuel and oxidant suffering from low Reynolds number condition in such a small combustor. In particular, the vortical flow region ahead of fuel jet plays an important role for rapid mixing. Discussion is made for the time and space averaged turbulent flow and scalar quantities which show peculiar characteristics corresponding to different vortical flow structures for each baffle plate shapes.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.27 no.9
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• pp.1282-1289
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• 2003

Transport of a scalar quantity, such as chemical concentration or temperature, is important in many engineering applications and environmental flows. Here we report on results obtained from the large eddy simulations of flow and concentration fields inside the tank performed using a spectral multi-domain technique. The computations were driven by specifying the impeller-induced flow at the blade tip radius (Yoon et al.). This study focused on the concentration development at different molecular diffusivities in a stirred tank operated under turbulent conditions. The main objective of the work presented here is to study the large-scale mixing structure at different molecular diffusivities in a stirred tank by using the large eddy simulation. The time sequence of concentration and flow fields shows the flow dependency of the concentration development. The presence of spatial inhomogenieties is detailed by observing the time variation oflocal concentration at different positions.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.28 no.11
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• pp.1407-1416
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• 2004

A two-dimensional direct numerical simulation was performed to investigate the flame structure of CH$_4$/$N_2$-Air counterflow nonpremixed flame interacting with a single vortex. The detailed transport properties and a modified 16-step augmented reduced mechanism based on Miller and Bowman's detailed chemistry were adopted in this computation. The results showed that an initially flat stagnation plane, on which an axial velocity was zero, was deformed into a complex-shaped plane, and an initial stagnation point was moved far away from a vortex head when the counterflow field was perturbed by the vortex. It was noted that the movement of stagnation point could alter the species transport mechanism to the flame surface. It was also identified that the altered species transport mechanism affected the distributions of the mixture fraction and the scalar dissipation rate.

• Journal of KIISE:Computing Practices and Letters
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• v.8 no.1
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• pp.107-115
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• 2002

We propose a new hybrid value predictor which achieves high performance by combining several predictors. Because the proposed hybrid value predictor can update the prediction table speculatively, it efficiently reduces the number of mispredicted instructions due to stale data. Also, the proposed predictor can enhance the prediction accuracy and efficiently decrease the hardware cost of predictor, because it allocates instructions into the best-suited predictor during instruction fetch stage by using the information of static classification which is obtained from the profile-based compiler implementation. For the 16-issue superscalar processors, simulation results based on the SimpleScalar/PISA tool set show that we achieve the average prediction rates of 73% by using speculative update and the average prediction rates of 88% by adding static classification for the SPECint95 benchmark programs.