• Computers and Concrete
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• v.25 no.2
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• pp.133-144
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• 2020

This paper aims to study vibration characteristics of chiral and zigzag double-walled carbon nanotubes entrenched on Donnell shell model. The Eringen's nonlocal elastic equations are being combined with Donnell shell theory to observe small scale response. Wave propagation is proposed technique to establish field equations of model subjected to four distinct end supports. A nonlocal model has been formulated to explore the frequency spectrum of both chiral and zigzag double-walled CNTs along with diversity of indices and nonlocal parameter. The significance of scale effect in relevance of length-to-diameter and thickness- to- radius ratios are discussed and displayed in detail. The numerical solution based on this nonlocal Donnell shell model can be further used to predict other frequency phenomena of double-walled and multi-walled CNTs.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.690-693
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• 2004

This paper proposes a multi-resolution electrostatic potential field (MREPF) based solution to the mobile robot path planning and collision avoidance problem in 2D dynamic environment. The MREPF is an environment method in calculation time and updating field map. The large scale resolution map is added to EPF and this resolution map interacts with the small scale resolution map to find an optimal solution in real time. This approach can be interpreted with Atlantis model. The simulation studies show the efficiency of the proposed algorithm.

• Journal of The Korean Astronomical Society
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• v.29 no.2
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• pp.83-91
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• 1996

We present a model that rotating primordial blackholes(PBHs) produced at the end of inflation generate the random, non-oriented primordial magnetic field. PBHs are copiously produced as the Universe completes the cosmic phase transition via bubble nucleation and tunneling processes in the extended inflation hypothesis. The PBHs produced acquire angular momentum through the mutual tidal gravitational interaction. For PBHs of mass less than 1013g, one can show that the evaporation (photon) luminosity of PBHs exceeds the Eddington limit. Thus throughout the lifetime of the rotating PBH, radiation flow from the central blackhole along the Kerr-geodesic exerts torque to ambient plasma. In the process similar to the Bierman's battery mechanism electron current reaching up to the horizon scale is induced. For PBHs of Grand Unified Theories extended inflation with the symmetry breaking temperature of $T_{GUT}\;\~\;10^{10}$ GeV, which evaporate near decoupling, we find that they generate random, non-oriented magnetic fields of $\~10^{-11}G$ on the last-scattering surface on (the present comoving) scales of $\~O(10)Mpc$.

• Journal of Information Display
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• v.5 no.1
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• pp.34-40
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• 2004

Time resolved infrared IR absorption spectroscopy is carried out to investigate the dynamics of electric field induced reorientation of the biphenyl molecular core and alkyl tail sub-fragments of the nematic liquid crystal 5CB (4-pentyl-4-cyano-biphenyl). The planar to homeotropic transition for high pre-tilt planar aligned cells, is studied for switching times ranging from 200 ${\mu}sec$ down to 80 ${\mu}sec$, the latter a factor of 1000 times faster than any previous nematic IR study. The reorientation rates of the core and tail are found to be the same to within experimental error and scale inversely with applied field squared, as expected for the balance of field and viscous torques. Thus any molecular conformation change during switching must relax on a shorter time scale. A simple model shows that no substantial differences exist between the reorientational dynamics of the tails and cores on the time scales longer than on the order of 10 ${\mu}s$.

• ETRI Journal
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• v.39 no.2
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• pp.284-291
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• 2017

Drain-induced barrier lowering (DIBL) is one of the main parameters employed to indicate the short-channel effect for nano metal-oxide semiconductor field-effect transistors (MOSFETs). We propose a new physical model of the DIBL effect under two-dimensional approximations based on the energy-conservation equation for channel electrons in FETs, which is different from the former field-penetration model. The DIBL is caused by lowering of the effective potential barrier height seen by the channel electrons because a lateral channel electric field results in an increase in the average kinetic energy of the channel electrons. The channel length, temperature, and doping concentration-dependent DIBL effects predicted by the proposed physical model agree well with the experimental data and simulation results reported in Nature and other journals.

• Journal of the Korean Society for Industrial and Applied Mathematics
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• v.20 no.1
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• pp.37-50
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• 2016

A large eddy simulation (LES) of a turbulent channel flow is performed by using the third order low-storage Runge-Kutta method in time and second order finite difference formulation in space with staggered grid at a Reynolds number, $Re_{\tau}=590$ based on the channel half width, ${\delta}$ and wall shear velocity, $u_{\tau}$. To reduce the calculation cost of LES, algebraic wall model (AWM) is applied to approximate the near-wall region. The computation is performed in a domain of $2{\pi}{\delta}{\times}2{\delta}{\times}{\pi}{\delta}$ with $32{\times}20{\times}32$ grid points. Standard Smagorinsky model is used for subgrid-scale (SGS) modeling. Essential turbulence statistics of the flow field are computed and compared with Direct Numerical Simulation (DNS) data and LES data using no wall model. Agreements as well as discrepancies are discussed. The flow structures in the computed flow field have also been discussed and compared with LES data using no wall model.

• Proceedings of the Korea Water Resources Association Conference
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• 2019.05a
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• pp.154-154
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• 2019

Characterization of reliable field-scale root-zone soil moisture (RZSM) variability contribute to effective hydro-meterological monitoring. Although a promising cosmic-ray neutron probe (CRNP) holds the pontential for field-scale RZSM measurement, it is often restricted at deeper depths due to the non-unique sensitivity of CRNP-measured fast neutron signal to other hydrogen pools. In this study, a merging framework relied on coupling cosmic-ray soil moisture with a representative additional RZSM, was introduced to scale shallower CRNP effective depth to represent root-zone layer. We tested our proposed framework over a densely vegetated region in South Korea covering a network of one CRNP and nine in-situ point measurements. In particular, cosmic-ray soil moisture and ancillary RZSM retrieved from the most time stable location were considered as input datasets; whereas the remaining point locations were used to generate a reference RZSM product. The errors between these two input datasets and the reference were forecasted by a linear autoregressive model. A linear combination of forecasts was then employed to compute a suitable weight for merging two input products from the predicted errors. The performance of merging framework was evaluated against reference RZSM in comparison to the two original products and a commonly used exponential filter technique. The results of this study showed that merging framework outperformed other products, demonstrating its robustness in improving field-scale RZSM. Moreover, a strong relationship between the quality of input data and the performance merging framework in light of CRNP effective depth variation has been also underlined via the merging framework.

• Geophysics and Geophysical Exploration
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• v.26 no.2
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• pp.84-93
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• 2023

The supervised learning-based deep-learning seismic inversion techniques have demonstrated successful performance in synthetic data examples targeting small-scale areas. The supervised learning-based deep-learning seismic inversion uses time-domain wavefields as input and subsurface velocity models as output. Because the time-domain wavefields contain various types of wave information, the data size is considerably large. Therefore, research applying supervised learning-based deep-learning seismic inversion trained with a significant amount of field-scale data has not yet been conducted. In this study, we predict subsurface velocity models using Laplace-domain wavefields as input instead of time-domain wavefields to apply a supervised learning-based deep-learning seismic inversion technique to field-scale data. Using Laplace-domain wavefields instead of time-domain wavefields significantly reduces the size of the input data, thereby accelerating the neural network training, although the resolution of the results is reduced. Additionally, a large grid interval can be used to efficiently predict the velocity model of the field data size, and the results obtained can be used as the initial model for subsequent inversions. The neural network is trained using only synthetic data by generating a massive synthetic velocity model and Laplace-domain wavefields of the same size as the field-scale data. In addition, we adopt a towed-streamer acquisition geometry to simulate a marine seismic survey. Testing the trained network on numerical examples using the test data and a benchmark model yielded appropriate background velocity models.

• Wind and Structures
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• v.13 no.6
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• pp.557-580
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• 2010

A new inflow turbulence generation method and a combined dynamic SGS model recently developed by the authors were applied to evaluate the wind effects on 508 m high Taipei 101 Tower. Unlike the majority of the past studies on large eddy simulation (LES) of wind effects on tall buildings, the present numerical simulations were conducted for the full-scale tall building with Reynolds number greater than $10^8$. The inflow turbulent flow field was generated based on the new method called discretizing and synthesizing of random flow generation technique (DSRFG) with a prominent feature that the generated wind velocity fluctuations satisfy any target spectrum and target profiles of turbulence intensity and turbulence integral length scale. The new dynamic SGS model takes both advantages of one-equation SGS model and a dynamic production term without test-filtering operation, which is particular suitable to relative coarse grid situations and high Reynolds number flows. The results of comparative investigations with and without generation of inflow turbulence show that: (1) proper simulation of an inflow turbulent field is essential in accurate evaluation of dynamic wind loads on a tall building and the prescribed inflow turbulence characteristics can be adequately imposed on the inflow boundary by the DSRFG method; (2) the DSRFG can generate a large number of random vortex-like patterns in oncoming flow, leading to good agreements of both mean and dynamic forces with wind tunnel test results; (3) The dynamic mechanism of the adopted SGS model behaves adequately in the present LES and its integration with the DSRFG technique can provide satisfactory predictions of the wind effects on the super-tall building.

• International Journal of Fluid Machinery and Systems
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• v.2 no.4
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• pp.353-362
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• 2009

In the process of turbine modernizations, the investigation of the influences of water passage roughness on radial flow machine performance is crucial and validates the efficiency step up between reduced scale model and prototype. This study presents the specific losses per component of a Francis turbine, which are estimated by CFD simulation. Simulations are performed for different water passage surface roughness heights, which represents the equivalent sand grain roughness height. As a result, the boundary layer logarithmic velocity profile still exists for rough walls, but moves closer to the wall. Consequently, the wall friction depends not only on roughness height but also on its shape and distribution. The specific losses are determined by CFD numerical simulations for each component of the prototype, taking into account its own specific sand grain roughness height. The model efficiency step up between reduced scale model and prototype value is finally computed by the assessment of specific losses on prototype and by evaluating specific losses for a reduced scale model with smooth walls. Furthermore, surveys of rough walls of each component were performed during the geometry recovery on the prototype and comparisons are made with experimental data from the EPFL Laboratory for Hydraulic Machines reduced scale model measurements. This study underlines that if rough walls are considered, the CFD approach estimates well the local friction loss coefficient. It is clear that by considering sand grain roughness heights in CFD simulations, its forms a significant part of the global performance estimation. The availability of the efficiency field measurements provides an unique opportunity to assess the CFD method in view of a systematic approach for turbine modernization step up evaluation. Moreover, this paper states that CFD is a very promising tool for future evaluation of turbine performance transposition from the scale model to the prototype.