• Title/Summary/Keyword: Multi-coupled

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Improving Strontium Isotope Ratio Analysis Using MC-ICP-MS (다검출기 유도결합 플라즈마 질량분석기를 이용한 스트론튬 동위원소비 분석법 개선)

  • Lee, Sin-Woo;Park, Jaeseon;Park, Hyun-Woo;Hwang, Jong Yeon;Kim, Kumhee;Chung, Hyun-Mi;Choi, Jong-Woo
    • Journal of Environmental Analysis, Health and Toxicology
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    • v.21 no.4
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    • pp.237-242
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    • 2018
  • Strontium (Sr) commonly exists in rock, groundwater, soil, plants, and animals. The Sr isotope ratio offers important information as a tracer on nature because the Sr isotopic composition is not fractionated by any biological process in these ecosystems. Hence, Sr isotope ratio has been used in several studies on tracing the Sr source for contaminated sites and human migration. In this study, we developed a separation method for Sr content, and then improved Sr isotope analysis using multi-collector inductively coupled plasma mass spectrometry (MC-ICP-MS). A powdered rock standard (NIST 2710a) was used to determine the removal of interference elements (Rb and Ca) and the recovery rate of Sr content. The results ranged from 98% to 106%. Additionally, three standard samples (NBS 987, IAPSO and NIST 1486) were analyzed to evaluate the precision and accuracy of the results. The measured $^{87}Sr/^{86}Sr$ ratio for all the samples were consistent with the reported values, within an error. These results indicate that our established Sr separation and Sr isotope measurement methods are reliable and can hence be useful in the fields of environmental and forensic sciences.

Improvement in Seasonal Prediction of Precipitation and Drought over the United States Based on Regional Climate Model Using Empirical Quantile Mapping (경험적 분위사상법을 이용한 지역기후모형 기반 미국 강수 및 가뭄의 계절 예측 성능 개선)

  • Song, Chan-Yeong;Kim, So-Hee;Ahn, Joong-Bae
    • Atmosphere
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    • v.31 no.5
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    • pp.637-656
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    • 2021
  • The United States has been known as the world's major producer of crops such as wheat, corn, and soybeans. Therefore, using meteorological long-term forecast data to project reliable crop yields in the United States is important for planning domestic food policies. The current study is part of an effort to improve the seasonal predictability of regional-scale precipitation across the United States for estimating crop production in the country. For the purpose, a dynamic downscaling method using Weather Research and Forecasting (WRF) model is utilized. The WRF simulation covers the crop-growing period (March to October) during 2000-2020. The initial and lateral boundary conditions of WRF are derived from the Pusan National University Coupled General Circulation Model (PNU CGCM), a participant model of Asia-Pacific Economic Cooperation Climate Center (APCC) Long-Term Multi-Model Ensemble Prediction System. For bias correction of downscaled daily precipitation, empirical quantile mapping (EQM) is applied. The downscaled data set without and with correction are called WRF_UC and WRF_C, respectively. In terms of mean precipitation, the EQM effectively reduces the wet biases over most of the United States and improves the spatial correlation coefficient with observation. The daily precipitation of WRF_C shows the better performance in terms of frequency and extreme precipitation intensity compared to WRF_UC. In addition, WRF_C shows a more reasonable performance in predicting drought frequency according to intensity than WRF_UC.

A computational estimation model for the subgrade reaction modulus of soil improved with DCM columns

  • Dehghanbanadaki, Ali;Rashid, Ahmad Safuan A.;Ahmad, Kamarudin;Yunus, Nor Zurairahetty Mohd;Said, Khairun Nissa Mat
    • Geomechanics and Engineering
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    • v.28 no.4
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    • pp.385-396
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    • 2022
  • The accurate determination of the subgrade reaction modulus (Ks) of soil is an important factor for geotechnical engineers. This study estimated the Ks of soft soil improved with floating deep cement mixing (DCM) columns. A novel prediction model was developed that emphasizes the accuracy of identifying the most significant parameters of Ks. Several multi-layer perceptron (MLP) models that were trained using the Levenberg Marquardt (LM) backpropagation method were developed to estimate Ks. The models were trained using a reliable database containing the results of 36 physical modelling tests. The input parameters were the undrained shear strength of the DCM columns, undrained shear strength of soft soil, area improvement ratio and length-to-diameter ratio of the DCM columns. Grey wolf optimization (GWO) was coupled with the MLPs to improve the performance indices of the MLPs. Sensitivity tests were carried out to determine the importance of the input parameters for prediction of Ks. The results showed that both the MLP-LM and MLP-GWO methods showed high ability to predict Ks. However, it was shown that MLP-GWO (R = 0.9917, MSE = 0.28 (MN/m2/m)) performed better than MLP-LM (R =0.9126, MSE =6.1916 (MN/m2/m)). This proves the greater reliability of the proposed hybrid model of MLP-GWO in approximating the subgrade reaction modulus of soft soil improved with floating DCM columns. The results revealed that the undrained shear strength of the soil was the most effective factor for estimation of Ks.

High-velocity ballistics of twisted bilayer graphene under stochastic disorder

  • Gupta, K.K.;Mukhopadhyay, T.;Roy, L.;Dey, S.
    • Advances in nano research
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    • v.12 no.5
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    • pp.529-547
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    • 2022
  • Graphene is one of the strongest, stiffest, and lightest nanoscale materials known to date, making it a potentially viable and attractive candidate for developing lightweight structural composites to prevent high-velocity ballistic impact, as commonly encountered in defense and space sectors. In-plane twist in bilayer graphene has recently revealed unprecedented electronic properties like superconductivity, which has now started attracting the attention for other multi-physical properties of such twisted structures. For example, the latest studies show that twisting can enhance the strength and stiffness of graphene by many folds, which in turn creates a strong rationale for their prospective exploitation in high-velocity impact. The present article investigates the ballistic performance of twisted bilayer graphene (tBLG) nanostructures. We have employed molecular dynamics (MD) simulations, augmented further by coupling gaussian process-based machine learning, for the nanoscale characterization of various tBLG structures with varying relative rotation angle (RRA). Spherical diamond impactors (with a diameter of 25Å) are enforced with high initial velocity (Vi) in the range of 1 km/s to 6.5 km/s to observe the ballistic performance of tBLG nanostructures. The specific penetration energy (Ep*) of the impacted nanostructures and residual velocity (Vr) of the impactor are considered as the quantities of interest, wherein the effect of stochastic system parameters is computationally captured based on an efficient Gaussian process regression (GPR) based Monte Carlo simulation approach. A data-driven sensitivity analysis is carried out to quantify the relative importance of different critical system parameters. As an integral part of this study, we have deterministically investigated the resonant behaviour of graphene nanostructures, wherein the high-velocity impact is used as the initial actuation mechanism. The comprehensive dynamic investigation of bilayer graphene under the ballistic impact, as presented in this paper including the effect of twisting and random disorder for their prospective exploitation, would lead to the development of improved impact-resistant lightweight materials.

An optimized deployment strategy of smart smoke sensors in a large space

  • Liu, Pingshan;Fang, Junli;Huang, Hongjun
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.16 no.11
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    • pp.3544-3564
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    • 2022
  • With the development of the NB-IoT (Narrow band Internet of Things) and smart cities, coupled with the emergence of smart smoke sensors, new requirements and issues have been introduced to study on the deployment of sensors in large spaces. Previous research mainly focuses on the optimization of wireless sensors in some monitoring environments, including three-dimensional terrain or underwater space. There are relatively few studies on the optimization deployment problem of smart smoke sensors, and leaving large spaces with obstacles such as libraries out of consideration. This paper mainly studies the deployment issue of smart smoke sensors in large spaces by considering the fire probability of fire areas and the obstacles in a monitoring area. To cope with the problems of coverage blind areas and coverage redundancy when sensors are deployed randomly in large spaces, we proposed an optimized deployment strategy of smart smoke sensors based on the PSO (Particle Swarm Optimization) algorithm. The deployment problem is transformed into a multi-objective optimization problem with many constraints of fire probability and barriers, while minimizing the deployment cost and maximizing the coverage accuracy. In this regard, we describe the structure model in large space and a coverage model firstly, then a mathematical model containing two objective functions is established. Finally, a deployment strategy based on PSO algorithm is designed, and the performance of the deployment strategy is verified by a number of simulation experiments. The obtained experimental and numerical results demonstrates that our proposed strategy can obtain better performance than uniform deployment strategies in terms of all the objectives concerned, further demonstrates the effectiveness of our strategy. Additionally, the strategy we proposed also provides theoretical guidance and a practical basis for fire emergency management and other departments to better deploy smart smoke sensors in a large space.

Future changes in runoff characteristics of an estuarine reservoir watershed using CMIP6 multi-GCMs (CMIP6 다중 GCMs을 적용한 담수호 유역의 미래 유출특성 변화)

  • Sinae Kim;Seokhyeon Kim;Hyunji Lee;Jihye Kwak;Jihye Kim;Moon-Seong Kang
    • Proceedings of the Korea Water Resources Association Conference
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    • 2023.05a
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    • pp.419-419
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    • 2023
  • 하천의 최종 유출부와 해양이 만나는 지점을 하구라고 하며, 우리나라는 주로 서해안 지역에 하구 방조제 건설에 따른 담수호가 조성되어 다양한 목적으로 수자원이 활용되고 있다. 이러한 하구 담수호는 바다로 유입되기 직전의 물을 저류시켜 수자원 확보에 긍정적이나, 일반적으로 유역의 최하류에 위치해 있어 오염물질 유입, 부영양화, 염분 침출로 인한 오염물질 용출 등에 취약하다. 따라서 담수호의 회복탄력성 향상과 지속가능한 수자원 관리를 위해서는 미래 기후변화에 따른 영향 분석이 필수적이다. 특히 기후변화는 거대규모의 홍수과 같은 자연재난, 농업가뭄 및 식생가뭄 등의 증가로 이어질 수 있으므로, 이에 효과적으로 대비하기 위해서는 미래 기후조건에 따른 하천의 미래 유출량 변화 예측이 수행되어야 한다. 본 연구에서는 불확실한 미래 수문변화를 예측하기 위해 CMIP6(Coupled Model Intercomparison Project Phase 6) GCMs(Global Climate Models)의 SSP(Shared Socioeconomic Pathways) 시나리오를 유역 유출모델에 적용하여 기후변화에 따른 미래 유출특성의 변화를 예측하였다. 충청남도 서산시에 위치한 간월호 유역을 대상유역으로 선정하고, HSPF(Hydrological Simulation Program-FORTRAN) 모형을 적용하여 상류유역의 과거 및 미래 장기유출량 모의를 수행하였다. 모의된 시나리오별 유출량을 기반으로 최빈유량곡선법을 적용하여 미래의 기준유량 발생시점 및 지속기간의 변화를 분석하였으며, CVDs(Center-of-volume dates)의 변화를 통해 기후변화에 따른 홍수기의 시기적 변화 양상을 파악하고자 하였다. 본 연구의 결과는 미래 유역 환경변화를 고려한 담수호의 수자원 보전관리계획 수립에 있어 기초자료로 활용될 수 있을 것으로 기대된다.

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Assessment of Historical and Future Climatic Trends in Seti-Gandaki Basin of Nepal. A study based on CMIP6 Projections

  • Bastola Shiksha;Cho Jaepil;Jung Younghun
    • Proceedings of the Korea Water Resources Association Conference
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    • 2023.05a
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    • pp.162-162
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    • 2023
  • Climate change is a complex phenomenon having its impact on diverse sectors. Temperature and precipitation are two of the most fundamental variables used to characterize climate, and changes in these variables can have significant impacts on ecosystems, agriculture, and human societies. This study evaluated the historical (1981-2010) and future (2011-2100) climatic trends in the Seti-Gandaki basin of Nepal based on 5 km resolution Multi Model Ensemble (MME) of 18 Global Climate Models (GCMs) from the Coupled Model Intercomparison Project Phase 6 (CMIP6) for SSP1-2.6, SSP2-4.5 and SSP5-85 scenarios. For this study, ERA5 reanalysis dataset is used for historical reference dataset instead of observation dataset due to a lack of good observation data in the study area. Results show that the basin has experienced continuous warming and an increased precipitation pattern in the historical period, and this rising trend is projected to be more prominent in the future. The Seti basin hosts 13 operational hydropower projects of different sizes, with 10 more planned by the government. Consequently, the findings of this study could be leveraged to design adaptation measures for existing hydropower schemes and provide a framework for policymakers to formulate climate change policies in the region. Furthermore, the methodology employed in this research could be replicated in other parts of the country to generate precise climate projections and offer guidance to policymakers in devising sustainable development plans for sectors like irrigation and hydropower.

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Development of the vapor film thickness correlation in porous corrosion deposits on the cladding in PWR

  • Yuan Shen;Zhengang Duan;Chuan Lu ;Li Ji ;Caishan Jiao ;Hongguo Hou ;Nan Chao;Meng Zhang;Yu Zhou;Yang Gao
    • Nuclear Engineering and Technology
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    • v.54 no.12
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    • pp.4798-4808
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    • 2022
  • The porous corrosion deposits (known as CRUD) adhered to the cladding have an important effect on the heat transfer from fuel rods to coolant in PWRs. The vapor film is the main constituent in the two-phase film boiling model. This paper presents a vapor film thickness correlation, associated with CRUD porosity, CRUD chimney density, CRUD particle size, CRUD thickness and heat flux. The dependences of the vapor film thickness on the various influential factors can be intuitively reflected from this vapor film thickness correlation. The temperature, pressure, and boric acid concentration distributions in CRUD can be well predicted using the two-phase film boiling model coupled with the vapor film thickness correlation. It suggests that the vapor thickness correlation can estimate the vapor film thickness more conveniently than the previously reported vapor thickness calculation methods.

Grouting diffusion mechanism in an oblique crack in rock masses considering temporal and spatial variation of viscosity of fast-curing grouts

  • Huang, Shuling;Pei, Qitao;Ding, Xiuli;Zhang, Yuting;Liu, Dengxue;He, Jun;Bian, Kang
    • Geomechanics and Engineering
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    • v.23 no.2
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    • pp.151-163
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    • 2020
  • Grouting method is an effective way of reinforcing cracked rock masses and plugging water gushing. Current grouting diffusion models are generally developed for horizontal cracks, which is contradictory to the fact that the crack generally occurs in rock masses with irregular spatial distribution characteristics in real underground environments. To solve this problem, this study selected a cement-sodium silicate slurry (C-S slurry) generally used in engineering as a fast-curing grouting material and regarded the C-S slurry as a Bingham fluid with time-varying viscosity for analysis. Based on the theory of fluid mechanics, and by simultaneously considering the deadweight of slurry and characteristics of non-uniform spatial distribution of viscosity of fast-curing grouts, a theoretical model of slurry diffusion in an oblique crack in rock masses at constant grouting rate was established. Moreover, the viscosity and pressure distribution equations in the slurry diffusion zone were deduced, thus quantifying the relationship between grouting pressure, grouting time, and slurry diffusion distance. On this basis, by using a 3-d finite element program in multi-field coupled software Comsol, the numerical simulation results were compared with theoretical calculation values, further verifying the effectiveness of the theoretical model. In addition, through the analysis of two engineering case studies, the theoretical calculations and measured slurry diffusion radius were compared, to evaluate the application effects of the model in engineering practice. Finally, by using the established theoretical model, the influence of cracking in rock masses on the diffusion characteristics of slurry was analysed. The results demonstrate that the inclination angle of the crack in rock masses and azimuth angle of slurry diffusion affect slurry diffusion characteristics. More attention should be paid to the actual grouting process. The results can provide references for determining grouting parameters of fast-curing grouts in engineering practice.

Analysis of Impacts of Aggressive Driving Events on Traffic Stream Using Driving and Traffic Simulations (주행 및 교통 시뮬레이션을 이용한 공격운전이 교통류에 미치는 영향 분석)

  • PARK, Subin;KIM, Yunjong;OH, Cheol;CHOI, Saerona
    • Journal of Korean Society of Transportation
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    • v.36 no.3
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    • pp.169-183
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    • 2018
  • Aggressive driving leads to a greater crash potential because it threatens surrounding vehicles. This study conducted traffic simulation experiments using driving behavior data obtained from multi-agent driving simulations. VISSIM traffic simulator and surrogate safety assessment model (SSAM) were used to identify the impacts of aggressive driving on traffic stream in terms of safety and operational efficiency. Market penetration rates (MPR) of aggressive driving vehicle, coupled with various traffic conditions, were taken into consideration in analyzing the impacts. As expected, it was identified that aggressive driving vehicles tended to deteriorate the traffic safety performance. From the perspective of operational efficiency, interesting results were observable. Under level of service (LOS) A, B, and C, it was observed that the average travel speed increased with greater MPRs. Conversely, the average travel speed decreased with under LOS D and E conditions. The outcome of this study would be effectively used for developing safety-related policies for reducing aggressive driving behavior.