• Journal of the Korean earth science society
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• v.39 no.4
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• pp.388-400
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• 2018

The purpose of this study was to explore the nine components of computational thinking (CT) practices and their operational definitions from the view of science education and to develop a CT practice framework that is going to be used as a planning and assessing tool for CT practice, as it is required for students to equip with in order to become creative problem solvers in $21^{st}$ century. We employed this framework into the earlier developed STEAM programs to see how it was valid and reliable. We first reviewed theoretical articles about CT from computer science and technology education field. We then proposed 9 components of CT as defined in technology education but modified operational definitions in each component from the perspective of science education. This preliminary CTPF (computational thinking practice framework) from the viewpoint of science education consisting of 9 components including data collection, data analysis, data representation, decomposing, abstraction, algorithm and procedures, automation, simulation, and parallelization. We discussed each component with operational definition to check if those components were useful in and applicable for science programs. We employed this CTPF into two different topics of STEAM programs to see if those components were observable with operational definitions. The profile of CT components within the selected STEAM programs for this study showed one sequential spectrum covering from data collection to simulation as the grade level went higher. The first three data related CT components were dominating at elementary level, all components of CT except parallelization were found at middle school level, and finally more frequencies in every component of CT except parallelization were also found at high school level than middle school level. On the basis of the result of CT usage in STEAM programs, we included 'generalization' in CTPF of science education instead of 'parallelization' which was not found. The implication about teacher education was made based on the CTPF in terms of science education.

• Nuclear Engineering and Technology
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• v.51 no.1
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• pp.13-30
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• 2019

This paper presents the recent improvements in the DeCART code for HTGR analysis. A new 190-group DeCART cross-section library based on ENDF/B-VII.0 was generated using the KAERI library processing system for HTGR. Two methods for the eigen-mode adjoint flux calculation were implemented. An azimuthal angle discretization method based on the Gaussian quadrature was implemented to reduce the error from the azimuthal angle discretization. A two-level parallelization using MPI and OpenMP was adopted for massive parallel computations. A quadratic depletion solver was implemented to reduce the error involved in the Gd depletion. A module to generate equivalent group constants was implemented for the nodal codes. The capabilities of the DeCART code were improved for geometry handling including an approximate treatment of a cylindrical outer boundary, an explicit border model, the R-G-B checker-board model, and a super-cell model for a hexagonal geometry. The newly improved and implemented functionalities were verified against various numerical benchmarks such as OECD/MHTGR-350 benchmark phase III problems, two-dimensional high temperature gas cooled reactor benchmark problems derived from the MHTGR-350 reference design, and numerical benchmark problems based on the compact nuclear power source experiment by comparing the DeCART solutions with the Monte-Carlo reference solutions obtained using the McCARD code.

• Structural Engineering and Mechanics
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• v.32 no.1
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• pp.95-126
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• 2009

The present contribution addresses the parallelization of advanced simulation methods for structural reliability analysis, which have recently been developed for large-scale structures with a high number of uncertain parameters. In particular, the Line Sampling method and the Subset Simulation method are considered. The proposed parallel algorithms exploit the parallelism associated with the possibility to simultaneously perform independent FE analyses. For the Line Sampling method a parallelization scheme is proposed both for the actual sampling process, and for the statistical gradient estimation method used to identify the so-called important direction of the Line Sampling scheme. Two parallelization strategies are investigated for the Subset Simulation method: the first one consists in the embarrassingly parallel advancement of distinct Markov chains; in this case the speedup is bounded by the number of chains advanced simultaneously. The second parallel Subset Simulation algorithm utilizes the concept of speculative computing. Speedup measurements in context with the FE model of a multistory building (24,000 DOFs) show the reduction of the wall-clock time to a very viable amount (<10 minutes for Line Sampling and ${\approx}$ 1 hour for Subset Simulation). The measurements, conducted on clusters of multi-core nodes, also indicate a strong sensitivity of the parallel performance to the load level of the nodes, in terms of the number of simultaneously used cores. This performance degradation is related to memory bottlenecks during the modal analysis required during each FE analysis.

• Journal of Broadcast Engineering
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• v.18 no.2
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• pp.178-184
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• 2013

In this paper, we propose an efficient parallelization technique of PU-level motion estimation (ME) in the next generation video coding standard, high efficiency video coding (HEVC) to reduce the time complexity of video encoding. It is difficult to encode video in real-time because ME has significant complexity (i.e., 80 percent at the encoder). In order to solve this problem, various techniques have been studied, and among them is the parallelization, which is carefully concerned in algorithm-level ME design. In this regard, merge estimation method using merge estimation region (MER) that enables ME to be designed in parallel has been proposed; but, parallel ME based on MER has still unconsidered problems to be implemented ideally in HEVC test model (HM). Therefore, we propose two strategies to implement stable parallel ME using MER in HM. Through experimental results, the excellence of our proposed methods is shown; the encoding time using the proposed method is reduced by 25.64 percent on average of that of HM which uses sequential ME.

• Nuclear Engineering and Technology
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• v.53 no.11
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• pp.3543-3562
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• 2021

The methods and performance of a 3D pin-by-pin neutronics code based on the 2D/1D decoupling method are presented. The code was newly developed as an effort to achieve enhanced accuracy and high calculation performance that are sufficient for the use in practical nuclear design analyses. From the 3D diffusion-based finite difference method (FDM) formulation, decoupled planar formulations are established by treating pre-determined axial leakage as a source term. The decoupled axial problems are formulated with the radial leakage source term. To accelerate the pin-by-pin calculation, the two-level coarse mesh finite difference (CMFD) formulation, which consists of the multigroup node-wise CMFD and the two-group assembly-wise CMFD is implemented. To enhance the accuracy, both the discontinuity factor method and the super-homogenization (SPH) factor method are examined for pin-wise cross-section homogenization. The parallelization is achieved with the OpenMP package. The accuracy and performance of the pin-by-pin calculations are assessed with the VERA and APR1400 benchmark problems. It is demonstrated that pin-by-pin 2D/1D alternating calculations within the two-level 3D CMFD framework yield accurate solutions in about 30 s for the typical commercial core problems, on a parallel platform employing 32 threads.

• Current Optics and Photonics
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• v.8 no.2
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• pp.138-150
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• 2024

This study is essential for advancing our knowledge about the interaction between long-range high-power lasers and energetic materials, with a particular emphasis on understanding the response of a 155-mm shell under various surface irradiations, taking into account external factors such as atmospheric disturbances. The analysis addresses known limitations in understanding the use of non-realistic targets and the negligence of ambient conditions. The model employs the three-dimensional level-set method, computer-aided design (CAD)-based target design, and a message-passing interface (MPI) parallelization scheme that enables rapid calculations of the complex chemical reactions of the irradiated high explosives. Important outcomes from interaction modeling include the accurate prediction of the initiation time of ignition, transient pressure, and temperature responses with the location of the initial hot spot within the shell, and the relative magnitude of noise with and without the presence of physical ambient disturbances. The initiation time of combustion was increased by approximately a factor of two with atmospheric disturbance considered, while slower heating of the target resulted in an average temperature rise of approximately 650 K and average pressure increase of approximately 1 GPa compared to the no ambient disturbance condition. The results provide an understanding of the interaction between the high-power laser and energetic target at a long distance in an atmospheric condition.

• Journal of Broadcast Engineering
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• v.17 no.5
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• pp.742-755
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• 2012

In this paper, we propose a parallel deblocking algorithm to resolve workload imbalance when the deblocking filter of high efficiency video coding (HEVC) decoder is parallelized. In HEVC, the deblocking filter which is one of the in-loop filters conducts two-step filtering on vertical edges first and horizontal edges later. The deblocking filtering can be conducted with high-speed through data-level parallelism because there is no dependency between adjacent edges for deblocking filtering processes. However, workloads would be imbalanced among regions even though the same amount of data for each region is allocated, which causes performance loss of decoder parallelization. In this paper, we solve the problem for workload imbalance by predicting the complexity of deblocking filtering with coding unit (CU) depth information at a coding tree block (CTB) and by allocating the same amount of workload to each core. Experimental results show that the proposed method achieves average time saving (ATS) by 64.3%, compared to single core-based deblocking filtering and also achieves ATS by 6.7% on average and 13.5% on maximum, compared to the conventional uniform data-level parallelism.