• Steel and Composite Structures
• /
• v.52 no.2
• /
• pp.199-215
• /
• 2024

The Caynarachi Bridge is a 130 m long posttensioned steel-concrete composite bridge built in Peru. The structural performance of this bridge under construction loads is reviewed in this paper using numerical simulation. Hence, a numerical model using shell finite elements to trace its deformational behavior at service conditions is proposed. The geometry and boundary conditions of the superstructure are updated according to the construction schedule. Firstly, the adequacy of the proposed model is validated with the field measurements obtained from the static truck load test. Secondly, the study of other scenarios less explored in research are performed to investigate the effect of some variables on bridge performance such as time effects, sequence of execution of concrete slabs and type of supports conditions at the abutments. The obtained results show that the original sequence of execution of the superstructure better behaves mechanically in relation to the other studied scenarios, yielding smaller stresses at critical cross sections with staging. It is also demonstrated that an improper slab staging may lead to more critical stresses at the studied cross sections and that casting the concrete slab at the negative moment regions first can lead to an optimal design. Also, the long-term displacements can be accurately predicted using an equivalent composite resistance cross section defined by a steel to concrete modulus ratio equal to three. This article gives some insights into the potential shortcomings or advantages of the original design through high-fidelity finite element simulations and reinforces the understating of posttensioned composite bridges with staging.

• KSCE Journal of Civil and Environmental Engineering Research
• /
• v.43 no.2
• /
• pp.175-185
• /
• 2023

As drought risk increases due to climate change, various research works are underway around the world to respond to drought so as to minimize drought damage. In particular, in recent years, many studies are focused on analyzing regional patterns of drought in a comprehensive manner, however there is still insufficient to quantitatively identify drought-risk areas in a large river basin considering climate change in Korea. In this study, we calculated the Standardized Precipitation Index (SPI) and the Modified Standardized Precipitation Index (M_SPI) as representative meteorological drought index, and performed spatial autocorrelation analysis to identify the drought hotspot region under climate change scenarios of Representative Concentration Pathway (RCP) 4.5 and RCP 8.5. The SPI was calculated by estimating parameters for each observation station within the study area, whereas the M_SPI was calculated by estimating parameters for the entire study area. It is more reasonable to use the M_SPI for assessing meteorological drought from an overall perspective within the study area. When the M_SPI was used, long-term droughts showed drought hotspot areas clearly larger than short-term droughts. In addition, the drought hotspot area moved from the center of the Nakdong River basin to the Seomjin River basin over time. Especially, the moving patterns of the short-term/long-term drought were apparent under the RCP 4.5, whereas the moving patterns of the long-term drought were distinct under the RCP 8.5 scenarios.

• Proceedings of the Korea Water Resources Association Conference
• /
• 2011.05a
• /
• pp.91-91
• /
• 2011

In the present study, the proposed EMD and NSOR models has been applied in hydrology and climate sciences. Here, we present those applications as the following: (1) to extend future scenarios of Global Surface Temperature Anomaly including long-term oscillation component; (2) to extend the future evolution of the Eastern Canada winter precipitation; (3) to apply EMD in detecting climate change.

• Journal of Korean Society for Atmospheric Environment
• /
• v.22 no.6
• /
• pp.912-921
• /
• 2006

This study examines greenhouse gas reduction potentials in cement manufacturing industry of Korea. An energy system model in the MARKAL (MARKet ALlocation) modeling framework was used in order to identify appropriate energy technologies and to quantify their possible implications In terms of greenhouse gas reduction. The model is characterized as mathematical tool for the long term energy system analysis provides an useful informations on technical assessment. Four scenarios are developed that covers the ti me span from 2000 to 2020. Being technology as a fundamental driving factor of the evolution of energy systems, it is essential to study the basic mechanisms of technological change and its role in developing more efficient, productive and clean energy systems. For this reasons, the learning curves on technologies for greenhouse gas reduction is specially considered. The analysis in this study shows that it is not easy to mitigate greenhouse gas with low cost in cement manufacturing industry under the current cap and trade method of Kyoto protocol.

• Wind and Structures
• /
• v.1 no.2
• /
• pp.145-160
• /
• 1998

In recent years, the effects of a possible climate change have been discussed in regard to wind loading on buildings and structures. Simple scenarios based on the assumption of global warming suggest an increase of storm intensities and storm frequencies and a possible re-distribution of storm tracks. Among recent publications, some papers seem to verify these scenarios while others deny the influence of climatic change. In an introductory step, the paper tries to re-examine these statements. Based on meteorological observations of a weather station in Germany, the existence of long-term trends and their statistical significance is investigated. The analysis itself is based on a refined model for the wind climate introducing a number of new basic variables. Thus, the numerical values of the design wind loads used in modern codes become more justified from the probabilistic point of view.

• International conference on construction engineering and project management
• /
• 2013.01a
• /
• pp.213-218
• /
• 2013

To respond to global warming and climate change, Korean Government has implemented the GHG Target Management, which leads to a voluntary reduction in greenhouse gases from large businesses. Korean universities have put efforts on reducing GHG emissions and energy consumptions in the campuses, however, because of various activities and its characteristic of non-profit organization, establishing a long-term plan for reducing greenhouse gases is necessary. In this research, the Seoul National University's energy usage is analyzed and applicable technologies for reducing GHG emissions are extracted. Hence, three scenarios for performing the GHG Target Management are established. Proposed scenario is available for GHG Target Management and it would be expected to support decision- makings for reducing GHG emissions.

• Proceedings of the Korea Water Resources Association Conference
• /
• 2021.06a
• /
• pp.69-69
• /
• 2021

From the unprecedented 2011 spring flood, the residens reside by Lake Champlain and Richelieu River encountered enormous damages. The International Joint Committee (IJC) released the Lake Champlain-Richelieu River (LCRR) Plan of Study (PoS). One of the major tasks for the PoS is to investigate the possible scenarios that might happen in the LCRR basin based on the stochastic simulation of the Net Basin Supplies that calculates the amount of flow into the lake and the river. Therefore, the current study proposed a novel apporach that simulate the annual NBS teleconnecting the climate index. The proposed model employed the bivariate empirical decomposition to contamporaneously model the long-term evolution of nonstationary oscillation embeded in the annual NBS and the climate signal (here, Artic Oscillation: AO). In order to represent the variational behavior of NBS correlation structure along with the temporal revolution of the climate index, a new nonstationary parameterization concept is proposed. The results indicate that the proposed model is superior performance in preserving long and short temporal correlation. It can even preserve the hurst coefficient better than any other tested models.

• Nuclear Engineering and Technology
• /
• v.54 no.10
• /
• pp.3878-3887
• /
• 2022

For the future energy-mix policy for carbon neutrality, demand for the capability of load-follow operation has emerged in nuclear power plants in order to accommodate the intermittency of renewable energy. The short-term decay heat analysis is also required to evaluate the decay heat level varied by the power level change during the load-follow operation, which is a very important parameter in terms of short-term decay heat removal during a grace time. In this study, the short-term decay heat level for 10 days after the shutdown was evaluated for both seasonal and daily load-follow cases. Additionally, the nuclide-wise contribution to the accumulated decay heat for 10 days was analyzed for further understanding of the short-term decay heat behavior. The result showed that in the seasonal case, the decay heat level was mainly determined by the power level right before the shutdown and the amount of each nuclide was varied with the power variation due to the long variation interval of 90 days. Whereas, in the daily case, the decay heat level was strongly impacted by the average power level during operation and meaningful mass variations for those nuclides were not observed due to the short variation interval of 0.5 days.

• 제어로봇시스템학회:학술대회논문집
• /
• 1997.10a
• /
• pp.1758-1761
• /
• 1997

The problem of long range capacity expansion planing for chemical processing network under uncertain demand forecast secnarios is addressed. This optimization problem involves capactiy expansion timing and sizing of each chemical processing unit to maximize the expected net present value considering the deviation of net present values and the excess capacity over a given time horizon. A multiperiod mixed integer nonlinear programming optimization model that is both solution and modle robust for any realization of demand scenarios is developed using the two-stage stochastic programming algorithm. Two example problems are considered to illustrate the effectiveness of the model.

• Ocean and Polar Research
• /
• v.37 no.1
• /
• pp.1-9
• /
• 2015

An approach based on the combined use of a 2D shallow water model and analytical 1D long wave run-up theory is proposed which facilitates the forecasting of tsunami run-up heights in a more rapid way, compared with the statistical or empirical run-up ratio method or resorting to complicated coastal inundation models. Its application is advantageous for long-term tsunami predictions based on the modeling of many prognostic tsunami scenarios. The modeling of the Chilean tsunami on February 27, 2010 has been performed, and the estimations of run-up heights are found to be in good agreement with available observations.