• KSCE Journal of Civil and Environmental Engineering Research
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• v.29 no.5B
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• pp.473-482
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• 2009

This study numerically discusses wave forces acting on a vertical wall such as breakwaters or revetments, subjected to incident undular or turbulent bores. Due to the complex hydrodynamics of bore, its wave forces have been predicted, mainly through laboratory experiments. Numerical simulations in this paper were carried out by CADMAS-SURF(CDIT, 2001), which is based on Navier-Stokes momentum equations and VOF method (Hirt and Nichols, 1981) for tracking free water surface. Its original source code was also partly revised to generate bore in the numerical water channel. Numerical raw data computed by CADMAS-SURF included great strong spike phenomena that show the abrupt jumps of wave loads. To resolve this undesired noise of raw data, the band-pass filter with the frequency of 5Hz was utilized. The filtered results showed reasonable agreements with the experimental results performed by Matsutomi (1991) and Ramsden (1996). It was confirmed that CADMASSURF can be applied to the design of coastal structures against tsunami bores. In addition, the transformation process and propagation speed of bores in the same 2-d water channel were discussed by the variations of water level for time and space. The numerical results indicated that the propagation speed of bore was changed due to the nonlinear interactions between negative and reflected waves.

• Journal of Energy Engineering
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• v.24 no.1
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• pp.164-171
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• 2015

Although coal-fired power generation has played a role as base load unit, it has incurred various social costs in the process of generating and providing electricity. It is necessary to extend the proportion of low-carbon power generations, and reduce the ratio of coal-fired power generation to cope with global climate changes. This study, therefore, attempts to estimate the public's willingness-to-pay (WTP) for substitution of supplied electricity from hydro-electricity generation, a representative renewable energy, for coal-fired power generation. To this end, we apply the contingent valuation (CV) method, widely used technique when valuing non-market goods, to elicit the public's WTP. In addition, a spike model is employed to consider zero WTPs. After the empirical analysis with 1,000 households CV survey data, the results show that mean household's WTP for replacing supplied electricity from hydro-electricity generation with coal-fired power generation is estimated to be about 54 KRW per kWh. The results of this study are expected to contribute to determining energy-mix and provide benefit information of hydro-electricity generation.

• Smart Media Journal
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• v.11 no.2
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• pp.77-83
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• 2022

The neuromorphic architecture uses a spiking neural network (SNN) model to derive more accurate results as more spike values are accumulated through inference experiments. When the inference result converges to a specific value, even if the inference experiment is further performed, the change in the result is smaller and power consumption may increase. In particular, in an AI-based IoT environment, power consumption can be a big problem. Therefore, in this paper, we propose a technique to reduce the power consumption of AI-based IoT by reducing the inference time by adjusting the inference image exposure time in the neuromorphic architecture environment. The proposed technique calculates the next inferred image exposure time by reflecting the change in inference accuracy. In addition, the rate of reflection of the change in inference accuracy can be adjusted with a coefficient value, and an optimal coefficient value is found through a comparison experiment of various coefficient values. In the proposed technique, the inference image exposure time corresponding to the target accuracy is greater than that of the linear technique, but the overall power consumption is less than that of the linear technique. As a result of measuring and evaluating the performance of the proposed method, it is confirmed that the inference experiment applying the proposed method can reduce the final exposure time by about 90% compared to the inference experiment applying the linear method.