• Nuclear Engineering and Technology
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• v.53 no.3
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• pp.732-740
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• 2021

Scattering resonance of medium mass nuclides leads complex spectrum in the fast reactor, which requires thousands of energy groups in the spectrum calculation. When the broad-group cross sections are collapsed, reaction rate cannot be completely conserved. To eliminate the error from energy collapsing, the Super-homogenization method in energy collapsing (ESPH) was employed in the fast reactor code SARAX. An ESPH factor was derived based on the ESPH-corrected SN transport equation. By applying the factor in problems with reflective boundary condition, both the effective multiplication factor and reaction rate were conserved. The fixed-source iteration was used to ensure the stability of ESPH iteration. However, in the energy collapsing process of SARAX, the vacuum boundary condition was adopted, which was necessary for fast reactors with strong heterogeneity. To further reduce the error caused by leakage, an additional conservation factor was proposed to correct the neutron current in energy collapsing. To evaluate the performance of ESPH with conservation factor, numerical benchmarks of fast reactors were calculated. The results of broad-group calculation agreed well with the direct full-core Monte-Carlo calculation, including the effective multiplication factor, radial power distribution, total control rod worth and sodium void worth.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.45 no.3
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• pp.123-130
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• 2022

Pair trading is a statistical arbitrage investment strategy. Traditionally, cointegration has been utilized in the pair exploring step to discover a pair with a similar price movement. Recently, the clustering analysis has attracted many researchers' attention, replacing the cointegration method. This study tests a clustering-driven pair trading investment strategy in the Korean stock market. If a pair detected through clustering has a large spread during the spread exploring period, the pair is included in the portfolio for backtesting. The profitability of the clustering-driven pair trading strategies is investigated based on various profitability measures such as the distribution of returns, cumulative returns, profitability by period, and sensitivity analysis on different parameters. The backtesting results show that the pair trading investment strategy is valid in the Korean stock market. More interestingly, the clustering-driven portfolio investments show higher performance compared to benchmarks. Note that the hierarchical clustering shows the best portfolio performance.

• Computers and Concrete
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• v.31 no.3
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• pp.223-239
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• 2023

Geometric nonlinear performance simulation and analysis of complex modern buildings and industrial products require high-performance shell elements. Balancing multiple aspects of performance in the one geometric nonlinear analysis element remains challenging. We present a new shell element, flat shell DKMGQ-CR (Co-rotational Discrete Kirchhoff-Mindlin Generalized Conforming Quadrilateral), for linear and geometric nonlinear analysis of both thick and thin shells. The DKMGQ-CR shell element was developed by combining the advantages of high-performance membrane and plate elements in a unified coordinate system and introducing the co-rotational formulation to adapt to large deformation analysis. The effectiveness of linear and geometric nonlinear analysis by DKMGQ-CR is verified through the tests of several classical numerical benchmarks. The computational results show that the proposed new element adapts to mesh distortion and effectively alleviates shear and membrane locking problems in linear and geometric nonlinear analysis. Furthermore, the DKMGQ-CR demonstrates high performance in analyzing thick and thin shells. The proposed element DKMGQ-CR is expected to provide an accurate, efficient, and convenient tool for the geometric nonlinear analysis of shells.

• ETRI Journal
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• v.44 no.6
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• pp.1034-1046
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• 2022

The learning-based multiview stereo (MVS) methods for three-dimensional (3D) reconstruction generally use 3D volumes for depth inference. The quality of the reconstructed depth maps and the corresponding point clouds is directly influenced by the spatial resolution of the 3D volume. Consequently, these methods produce point clouds with sparse local regions because of the lack of the memory required to encode a high volume of information. Here, we apply the atrous spatial pyramid pooling (ASPP) module in MVS methods to obtain dense feature maps with multiscale, long-range, contextual information using high receptive fields. For a given 3D volume with the same spatial resolution as that in the MVS methods, the dense feature maps from the ASPP module encoded with superior information can produce dense point clouds without a high memory footprint. Furthermore, we propose a 3D loss for training the MVS networks, which improves the predicted depth values by 24.44%. The ASPP module provides state-of-the-art qualitative results by constructing relatively dense point clouds, which improves the DTU MVS dataset benchmarks by 2.25% compared with those achieved in the previous MVS methods.

• Nuclear Engineering and Technology
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• v.55 no.8
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• pp.2785-2796
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• 2023

How to generate the precise broad group cross section is important for the fast reactor design. In this study, a fast reactor multi-group cross-section generation code MGGC2.0 are developed in-house for processing ultrafine group MATXS format library. Validation and verification are performed for MGGC2.0 code by applying the benchmarks of ICSBEP handbook, and the results of MGGC2.0 agree well with that of MCNP. The consistent P_N method with critical buckling search is in good agreement that condensed with TWODANT flux and flux moment for the inner core and outer core region. For the radial blanket and reflector, two region approximation method has been applied in MGGC2.0 by using collision Probability Method neutron flux solver. The RBEC-M benchmark was used to verify the power distribution calculation, and the relative error of power distribution comparison with the reference are less than 0.8% in the fuel region and the maximum relative error is 5.58% in the reflector region. Therefore, the precise broad cross section can be generated by MGGC2.0 for fast reactor.

• International conference on construction engineering and project management
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• 2009.05a
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• pp.40-40
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• 2009

Construction firms have long sought success in the global construction market through diversifying revenue sources and project portfolios. The volume of international contracts has contributed to firms' sustained growth by mitigating the impact of the domestic market's cyclical nature. In spite of the importance of international construction, the uncertainty and dynamic changes surrounding global construction pose serious threats to global contactors. Over the last decade, the international construction industry has changed drastically in many ways, particularly including financial resource diversity, competition rules for the selection of contractors, and the terms of delivery systems requiring more competent total service providers. This paper investigates the important changes for global contractors through various documentation analysis as well as in-depth interviews with industry experts. This paper then analyzes the common strategies and lessons obtained from the cases of leading global contractors that have sustained their growth in the competitive global construction during the last decade. In addition, the authors further analyzed the comparisons between those firms and Korean contractors to discern any difference in sustaining their growth in the competitive market. It was found that those leading firms were quite proactive and responsive to changing markets by diversifying their market revenues to stabilize their revenue structure and enhancing their competency through a wide range of 'business convergence'. In addition, they significantly increased their upstream/downstream functional capabilities; hence becoming more competent service providers, able to grow in these rapidly changing market conditions. Finally, this paper benchmarks the critical strategies that support growth, which in turn can provide a strategic guideline for expansion into the global construction market.

• Nuclear Engineering and Technology
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• v.55 no.9
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• pp.3213-3228
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• 2023

As an important part of the digital reactor, the pin-by-pin wise fine coupling calculation is a research hotspot in the field of nuclear engineering in recent years. It provides more precise and realistic simulation results for reactor design, operation and safety evaluation. CORCA-K a nodal code is redeveloped as a robust pin-by-pin wise neutronics and thermal-hydraulic coupled calculation code for pressurized water reactor (PWR) core. The nodal green's function method (NGFM) is used to solve the three-dimensional space-time neutron dynamics equation, and the single-phase single channel model and one-dimensional heat conduction model are used to solve the fluid field and fuel temperature field. The mesh scale of reactor core simulation is raised from the nodal-wise to the pin-wise. It is verified by two benchmarks: NEACRP 3D PWR and PWR MOX/UO₂. The results show that: 1) the pin-by-pin wise coupling calculation system has good accuracy and can accurately simulate the key parameters in steady-state and transient coupling conditions, which is in good agreement with the reference results; 2) Compared with the nodal-wise coupling calculation, the pin-by-pin wise coupling calculation improves the fuel peak temperature, the range of power distribution is expanded, and the lower limit is reduced more.

• Journal of Practical Agriculture & Fisheries Research
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• v.13 no.1
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• pp.3-17
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• 2011

Pipelines of processor have been growing deeper and issue widths wider over the years. If this trend continues, branch misprediction penalty will become very high. Branch misprediction is the single most significant performance limiter for improving processor performance using deeper pipelining. Therefore, more accurate branch predictor becomes an essential part of modem processors for FAFF(Food, Agriculture, Forestry, Fisheries)Information Processing. In this paper, we propose a branch prediction mechanism, using variable length history, which predicts using a bank having higher prediction accuracy among predictions from five banks. Bank 0 is a bimodal predictor which is indexed with the 12 least significant bits of the branch PC. Banks 1,2,3 and 4 are predictors which are indexed with different global history bits and the branch PC. In simulation results, the proposed mechanism outperforms gshare predictors using fixed history length of 12 and 13, up to 6.34% in prediction accuracy. Furthermore, the proposed mechanism outperforms gshare predictors using best history lengths for benchmarks, up to 2.3% in prediction accuracy.

• Geomechanics and Engineering
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• v.34 no.3
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• pp.285-301
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• 2023

During the construction of E75 highway through Grdelica gorge in Serbia, a major failure occurred in the zone of reinforced rock slope. Excavation was performed in highly anisotropic Paleozoic schist rock formation. The reinforcement consisted of the two rows of micropile wall with pre-stressed anchors. Forces in anchors were monitored with load cells while benchmarks were installed for superficial displacement measurements. The aim of the study is to investigate possible causes of instability considering different probability distributions of the strength of discontinuities and anchor bond strength by applying different optimization techniques for finding the critical failure surface. Even though the deterministic safety factor value is close to unity, the probability of failure is governed by variability of shear strength of anisotropic planes and optimization method used for locating the critical sliding surface. The Cuckoo search technique produces higher failure probabilities compared to the others. Depending on the assigned statistical distribution of input parameters, various performance functions of the factor of safety are obtained. The probability of failure is insensitive to the variation of bond strength. Different sampling techniques should yield similar results considering that the sufficient number of safety factor evaluations is chosen to achieve converged solution.

• Steel and Composite Structures
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• v.45 no.2
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• pp.281-291
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• 2022

Surmounting complexities in analyzing the mechanical parameters of concrete entails selecting an appropriate methodology. This study integrates a novel metaheuristic technique, namely satin bowerbird optimizer (SBO) with artificial neural network (ANN) for predicting uniaxial compressive strength (UCS) of concrete. For this purpose, the created hybrid is trained and tested using a relatively large dataset collected from the published literature. Three other new algorithms, namely Henry gas solubility optimization (HGSO), sunflower optimization (SFO), and vortex search algorithm (VSA) are also used as benchmarks. After attaining a proper population size for all algorithms, the Utilizing various accuracy indicators, it was shown that the proposed ANN-SBO not only can excellently analyze the UCS behavior, but also outperforms all three benchmark hybrids (i.e., ANN-HGSO, ANN-SFO, and ANN-VSA). In the prediction phase, the correlation indices of 0.87394, 0.87936, 0.95329, and 0.95663, as well as mean absolute percentage errors of 15.9719, 15.3845, 9.4970, and 8.0629%, calculated for the ANN-HGSO, ANN-SFO, ANN-VSA, and ANN-SBO, respectively, manifested the best prediction performance for the proposed model. Also, the ANN-VSA achieved reliable results as well. In short, the ANN-SBO can be used by engineers as an efficient non-destructive method for predicting the UCS of concrete.