• Title/Summary/Keyword: Mitigation Model

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Effects of District Energy Supply by Combined Heat and Power Plant on Greenhouse Gas Emission Mitigation (열병합발전을 이용한 집단에너지사업의 온실가스 감축효과)

  • Shin, Kyoung-A;Dong, Jong-In;Kang, Jae-Sung;Im, Yong-Hoon;Kim, Da-Hye
    • Journal of Climate Change Research
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    • v.8 no.3
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    • pp.213-220
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    • 2017
  • The purpose of this study is to analyze effects of Greenhouse Gas (GHG) emission reduction in district energy business mainly based on Combined Heat and Power (CHP) plants. Firstly this paper compares the actual carbon intensity of power production between conventional power plants and district energy plants. To allocate the GHG from CHP plants, two of different methods which were Alternative Generation Method and Power Bonus Method, have been investigated. The carbon intensity of power production in district energy plants ($0.43tonCO_2e/MWh$) was relatively lower than conventional gas-fired power plants ($0.52tonCO_2e/MWh$). Secondly we assessed the cost effectiveness of reduction by district energy sector compared to the other means using TIMES model method. We find that GHG marginal abatement cost of 'expand CHP' scenario (-$134/ton$CO_2$) is even below than renewable energy scenario such as photovoltaic power generation ($87/ton$CO_2$). Finally the GHG emission reduction potential was reviewed on the projected GHG emission emitted when the same amount of energy produced in combination of conventional power plants and individual boilers as substitution of district energy. It showed there were 10.1~41.8% of GHG emission reduction potential in district energy compared to the combination of conventional power plants and individual boilers.

Seismic damage mitigation of bridges with self-adaptive SMA-cable-based bearings

  • Zheng, Yue;Dong, You;Chen, Bo;Anwar, Ghazanfar Ali
    • Smart Structures and Systems
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    • v.24 no.1
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    • pp.127-139
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    • 2019
  • Residual drifts after an earthquake can incur huge repair costs and might need to replace the infrastructure because of its non-reparability. Proper functioning of bridges is also essential in the aftermath of an earthquake. In order to mitigate pounding and unseating damage of bridges subjected to earthquakes, a self-adaptive Ni-Ti shape memory alloy (SMA)-cable-based frictional sliding bearing (SMAFSB) is proposed considering self-adaptive centering, high energy dissipation, better fatigue, and corrosion resistance from SMA-cable component. The developed novel bearing is associated with the properties of modularity, replaceability, and earthquake isolation capacity, which could reduce the repair time and increase the resilience of highway bridges. To evaluate the super-elasticity of the SMA-cable, pseudo-static tests and numerical simulation on the SMA-cable specimens with a diameter of 7 mm are conducted and one dimensional (1D) constitutive hysteretic model of the SMAFSB is developed considering the effects of gap, self-centering, and high energy dissipation. Two types of the SMAFSB (i.e., movable and fixed SMAFSBs) are applied to a two-span continuous reinforced concrete (RC) bridge. The seismic vulnerabilities of the RC bridge, utilizing movable SMAFSB with the constant gap size of 60 mm and the fixed SMAFSBs with different gap sizes (e.g., 0, 30, and 60 mm), are assessed at component and system levels, respectively. It can be observed that the fixed SMAFSB with a gap of 30 mm gained the most retrofitting effect among the three cases.

Cyber Kill Chain-Based Taxonomy of Advanced Persistent Threat Actors: Analogy of Tactics, Techniques, and Procedures

  • Bahrami, Pooneh Nikkhah;Dehghantanha, Ali;Dargahi, Tooska;Parizi, Reza M.;Choo, Kim-Kwang Raymond;Javadi, Hamid H.S.
    • Journal of Information Processing Systems
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    • v.15 no.4
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    • pp.865-889
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    • 2019
  • The need for cyber resilience is increasingly important in our technology-dependent society where computing devices and data have been, and will continue to be, the target of cyber-attackers, particularly advanced persistent threat (APT) and nation-state/sponsored actors. APT and nation-state/sponsored actors tend to be more sophisticated, having access to significantly more resources and time to facilitate their attacks, which in most cases are not financially driven (unlike typical cyber-criminals). For example, such threat actors often utilize a broad range of attack vectors, cyber and/or physical, and constantly evolve their attack tactics. Thus, having up-to-date and detailed information of APT's tactics, techniques, and procedures (TTPs) facilitates the design of effective defense strategies as the focus of this paper. Specifically, we posit the importance of taxonomies in categorizing cyber-attacks. Note, however, that existing information about APT attack campaigns is fragmented across practitioner, government (including intelligence/classified), and academic publications, and existing taxonomies generally have a narrow scope (e.g., to a limited number of APT campaigns). Therefore, in this paper, we leverage the Cyber Kill Chain (CKC) model to "decompose" any complex attack and identify the relevant characteristics of such attacks. We then comprehensively analyze more than 40 APT campaigns disclosed before 2018 to build our taxonomy. Such taxonomy can facilitate incident response and cyber threat hunting by aiding in understanding of the potential attacks to organizations as well as which attacks may surface. In addition, the taxonomy can allow national security and intelligence agencies and businesses to share their analysis of ongoing, sensitive APT campaigns without the need to disclose detailed information about the campaigns. It can also notify future security policies and mitigation strategy formulation.

Performance Improvement in Single-Phase Electric Spring Control

  • Wang, Qingsong;Zuo, Wujian;Cheng, Ming;Deng, Fujin;Buja, Giuseppe
    • Journal of Power Electronics
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    • v.19 no.3
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    • pp.784-793
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    • 2019
  • Two objectives can be pursued simultaneously with the ${\delta}$ control of a single-phase electric spring (ES). These objectives are the stabilization of the voltage across the critical load (CL) of a power system, and the achievement of a specific functionality similar to the pure compensation of reactive power or the correction of the power factor. However, existing control systems implementing the ${\delta}$ control do not cope with non-ideal operating conditions, such as line voltage distortions, and exhibit a somewhat sluggish regulation of the CL voltage. In an effort to improve both the steady-state and transient performances of an ES power system, this paper proposes implementing the ${\delta}$ control by means of a control system built up on the repetitive control and assisted by state feedback with pole assignment. This paper starts by analyzing the dynamics of an ES power system in terms of its poles and zeros. After that, a reduced second-order model of the dynamics is formulated to avoid a notch filter in the pole assignment. A repetitive control for an ES power system is then designed to meet the two above mentioned objectives. Experimental tests carried out on a laboratory setup demonstrate the effectiveness of the proposed control system in significantly improving the ES power system performance, while reaching the two objectives. In particular, the tests outline the large mitigation of harmonics in the CL voltage under line voltage distortions and its fast stabilization action.

Non-linearity Mitigation Method of Particulate Matter using Machine Learning Clustering Algorithms (기계학습 군집 알고리즘을 이용한 미세먼지 비선형성 완화방안)

  • Lee, Sang-gwon;Cho, Kyoung-woo;Oh, Chang-heon
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2019.05a
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    • pp.341-343
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    • 2019
  • As the generation of high concentration particulate matter increases, much attention is focused on the prediction of particulate matter. Particulate matter refers to particulate matter less than $10{\mu}m$ diameter in the atmosphere and is affected by weather changes such as temperature, relative humidity and wind speed. Therefore, various studies have been conducted to analyze the correlation with weather information for particulate matter prediction. However, the nonlinear time series distribution of particulate matter increases the complexity of the prediction model and can lead to inaccurate predictions. In this paper, we try to mitigate the nonlinear characteristics of particulate matter by using cluster algorithm and classification algorithm of machine learning. The machine learning algorithms used are agglomerative clustering, density-based spatial clustering of applications with noise(DBSCAN).

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Sensitivity analysis of input variables to establish fire damage thresholds for redundant electrical panels

  • Kim, Byeongjun;Lee, Jaiho;Shin, Weon Gyu
    • Nuclear Engineering and Technology
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    • v.54 no.1
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    • pp.84-96
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    • 2022
  • In the worst case, a temporary ignition source (also known as transient combustibles) between two electrical panels can damage both panels. Mitigation strategies for electrical panel fires were previously developed using fire modeling and risk analysis. However, since they do not comply with deterministic fire protection requirements, it is necessary to analyze the boundary values at which combustibles may damage targets depending on various factors. In the present study, a sensitivity analysis of input variables related to the damage threshold of two electrical panels was performed for dimensionless geometry using a Fire Dynamics Simulator (FDS). A new methodology using a damage evaluation map was developed to assess the damage of the electrical panel. The input variables were the distance between the electrical panels, the vertical height of the fuel, the size of the fire, the wind speed and the wind direction. The heat flux was determined to increase as the vertical distance between the fuel and the panel decreased, and the largest heat flux was predicted when the vertical separation distance divided by one half flame length was 0.3-0.5. As the distance between the panels increases, the heat flux decreases according to the power law, and damage can be avoided when the distance between the fuel and the panel is twice the length of the panel. When the wind direction is east and south, to avoid damage to the electrical panel the distance must be increased by 1.5 times compared to no wind. The present scale model can be applied to any configuration where combustibles are located between two electrical panels, and can provide useful guidance for the design of redundant electrical panels.

3D Numerical investigation of a rounded corner square cylinder for supercritical flows

  • Vishwanath, Nivedan;Saravanakumar, Aditya K.;Dwivedi, Kush;Murthy, Kalluri R.C.;Gurugubelli, Pardha S.;Rajasekharan, Sabareesh G.
    • Wind and Structures
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    • v.35 no.1
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    • pp.55-66
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    • 2022
  • Tall buildings are often subjected to steady and unsteady forces due to external wind flows. Measurement and mitigation of these forces becomes critical to structural design in engineering applications. Over the last few decades, many approaches such as modification of the external geometry of structures have been investigated to mitigate wind-induced load. One such proven geometric modification involved the rounding of sharp corners. In this work, we systematically analyze the impact of rounded corner radii on the reducing the flow-induced loading on a square cylinder. We perform 3-Dimensional (3D) simulations for high Reynolds number flows (Re=1 × 105) which are more likely to be encountered in practical applications. An Improved Delayed Detached Eddy Simulation (IDDES) method capable of capturing flow accurately at large Reynolds numbers is employed in this study. The IDDES formulation uses a k-ω Shear Stress Transport (SST) model for near-wall modelling that prevents mesh-induced separation of the boundary layer. The effects of these corner modifications are analyzed in terms of the resulting variations in the mean and fluctuating components of the aerodynamic forces compared to a square cylinder with no geometric changes. Plots of the angular distribution of the mean and fluctuating coefficient of pressure along the square cylinder's surface illustrate the effects of corner modifications on the different parts of the cylinder. The windward corner's separation angle was observed to decrease with an increase in radius, resulting in a narrower and longer recirculation region. Furthermore, with an increase in radius, a reduction in the fluctuating lift, mean drag, and fluctuating drag coefficients has been observed.

A case study of gust factor characteristics for typhoon Morakat observed by distributed sites

  • Liu, Zihang;Fang, Genshen;Zhao, Lin;Cao, Shuyang;Ge, Yaojun
    • Wind and Structures
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    • v.35 no.1
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    • pp.21-34
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    • 2022
  • Gust factor is an important parameter for the conversion between peak gust wind and mean wind speed used for the structural design and wind-related hazard mitigation. The gust factor of typhoon wind is observed to show a significant dispersion and some differences with large-scale weather systems, e.g., monsoons and extratropical cyclones. In this study, insitu measurement data captured by 13 meteorological towers during a strong typhoon Morakot are collected to investigate the statistical characteristics, height and wind speed dependency of the gust factor. Onshore off-sea and off-land winds are comparatively studied, respectively to characterize the underlying terrain effects on the gust factor. The theoretical method of peak factor based on Gaussian assumption is then introduced to compare the gust factor profiles observed in this study and given in some building codes and standards. The results show that the probability distributions of gust factor for both off-sea winds and off-land winds can be well described using the generalized extreme value (GEV) distribution model. Compared with the off-land winds, the off-sea gust factors are relatively smaller, and the probability distribution is more leptokurtic with longer tails. With the increase of height, especially for off-sea winds, the probability distributions of gust factor are more peaked and right-tailed. The scatters of gust factor decrease with the mean wind speed and height. AS/NZ's suggestions are nearly parallel with the measured gust factor profiles below 80m, while the fitting curve of off-sea data below 120m is more similar to AIJ, ASCE and EU.

A Systems Engineering Approach for Predicting NPP Response under Steam Generator Tube Rupture Conditions using Machine Learning

  • Tran Canh Hai, Nguyen;Aya, Diab
    • Journal of the Korean Society of Systems Engineering
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    • v.18 no.2
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    • pp.94-107
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    • 2022
  • Accidents prevention and mitigation is the highest priority of nuclear power plant (NPP) operation, particularly in the aftermath of the Fukushima Daiichi accident, which has reignited public anxieties and skepticism regarding nuclear energy usage. To deal with accident scenarios more effectively, operators must have ample and precise information about key safety parameters as well as their future trajectories. This work investigates the potential of machine learning in forecasting NPP response in real-time to provide an additional validation method and help reduce human error, especially in accident situations where operators are under a lot of stress. First, a base-case SGTR simulation is carried out by the best-estimate code RELAP5/MOD3.4 to confirm the validity of the model against results reported in the APR1400 Design Control Document (DCD). Then, uncertainty quantification is performed by coupling RELAP5/MOD3.4 and the statistical tool DAKOTA to generate a large enough dataset for the construction and training of neural-based machine learning (ML) models, namely LSTM, GRU, and hybrid CNN-LSTM. Finally, the accuracy and reliability of these models in forecasting system response are tested by their performance on fresh data. To facilitate and oversee the process of developing the ML models, a Systems Engineering (SE) methodology is used to ensure that the work is consistently in line with the originating mission statement and that the findings obtained at each subsequent phase are valid.

Alleviation of γ-enolase decrease by the chlorogenic acid administration in the stroke animal model (뇌졸중에서 클로로겐산 투여에 의한 γ-enolase 감소 완화 효과)

  • Ju-Bin Kang;Murad Ali Shah;Min-Seo Ko;Phil-Ok Koh
    • Korean Journal of Veterinary Research
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    • v.63 no.1
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    • pp.6.1-6.9
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    • 2023
  • Stroke is a major cause of death and long-term disability. Chlorogenic acid is a phenolic compound with a potent neuroprotective effect. γ-enolase is a phosphopyruvate hydratase found in mature neurons and plays an important role in neuronal survival. This study investigated whether chlorogenic acid regulates the expression of γ-enolase during cerebral ischemia. Middle cerebral artery occlusion (MCAO) was performed to induce cerebral ischemia. Adult male rats were used and chlorogenic acid (30 mg/kg) or phosphate buffered saline (PBS) was injected intraperitoneally 2 hours after MCAO surgery. Cerebral cortical tissues were collected 24 hours after MCAO surgery. Our proteomic approach identified the reduction of γ-enolase caused by MCAO damage and the mitigation of this reduction by chlorogenic acid treatment. Results of reverse transcription-polymerase chain reaction and Western blot analyses showed a decrease in γ-enolase expression in the PBS-treated MCAO group. However, chlorogenic acid treatment attenuated this decrease. Results of immunofluorescence staining showed the change of γ-enolase by chlorogenic acid treatment. These results demonstrated that chlorogenic acid regulates the γ-enolase expression during MCAO-induced ischemia. Therefore, we suggest that chlorogenic acid mediates the neuroprotective function by regulating the γ-enolase expression in cerebral ischemia and may be used as a therapeutic agent for brain diseases including stroke.