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| 1 | Multiple Tuned Mass Damper Based Vibration Mitigation of Offshore Wind Turbine Considering Soil–Structure Interaction显示文摘The dynamics of jacket supported offshore wind turbine(OWT) in earthquake environment is one of the progressing focuses in the renewable energy field. Soil–structure interaction(SSI) is a fundamental principle to analyze stability and safety of the structure. This study focuses on the performance of the multiple tuned mass damper(MTMD) in minimizing the dynamic responses of the structures objected to seismic loads combined with static wind and wave loads. Response surface methodology(RSM) has been applied to design the MTMD parameters. The analyses have been performed under two different boundary conditions: fixed base(without SSI) and flexible base(with SSI). Two vibration modes of the structure have been suppressed by multi-mode vibration control principle in both cases. The effectiveness of the MTMD in reducing the dynamic response of the structure is presented. The dynamic SSI plays an important role in the seismic behavior of the jacket supported OWT, especially resting on the soft soil deposit.Finally, it shows that excluding the SSI effect could be the reason of overestimating the MTMD performance. | Mosaruf HUSSAN Faria SHARMIN Dookie KIM | 2017 | China Ocean Engineering2017，31，4： | 5 |
| 2 | Kinetic study on catalytic gasification of a modified sludge fuel显示文摘A new type of mixture fuel, sludge-oil-coal agglomerate (SOCA), was catalytically gasified with steam in a thermobalance reactor under atmospheric pressure. All the four catalysts studied (K2CO3, CaO, NiO and Fe2O3) were found capable of enhancing the steam gasification rate and significantly increasing the conversion of carbon. The ranking of catalytic activity was found to be K2CO3 CaO > NiO > Fe2O3. A modified volumetric-reaction model in the literature was used to describe the conversion behavior of the steam gasification studied by evaluating the kinetic parameters. Expressions of the apparent gasification rates for SOCA were presented for the design of catalytic gasification processes. | Byungho Song Dookie Kim Seungjae Lee Seokku Jeon Youngtai Choi Yoonseop Byoun Woonsig Moon Joonghee Lee Honggun Kim Hongki Lee Joongpyo Shim | 2008 | Particuology2008，6，4： | 4 |
| 3 | Prediction of Compressive Strength of Self-Compacting Concrete Using Intelligent Computational Modeling显示文摘In the present scenario,computational modeling has gained much importance for the prediction of the properties of concrete.This paper depicts that how computational intelligence can be applied for the prediction of compressive strength of Self Compacting Concrete(SCC).Three models,namely,Extreme Learning Machine(ELM),Adaptive Neuro Fuzzy Inference System(ANFIS)and Multi Adaptive Regression Spline(MARS)have been employed in the present study for the prediction of compressive strength of self compacting concrete.The contents of cement(c),sand(s),coarse aggregate(a),fly ash(f),water/powder(w/p)ratio and superplasticizer(sp)dosage have been taken as inputs and 28 days compressive strength(fck)as output for ELM,ANFIS and MARS models.A relatively large set of data including 80 normalized data available in the literature has been taken for the study.A comparison is made between the results obtained from all the above-mentioned models and the model which provides best fit is established.The experimental results demonstrate that proposed models are robust for determination of compressive strength of self-compacting concrete. | Susom Dutta ARamachandra Murthy Dookie Kim Pijush Samui | 2017 | Computers, Materials & Continua2017，，2： | 3 |
| 4 | Effect of enteric coating on antiplatelet activity of low-dose aspirin in healthy volunteers显示文摘 | Cox D Maree AO Dookie M | | 0，，08： | 1 |
| 5 | Bacterial entropathogens and antimicrobial susceptibility in children with acute diarrhea In Babol, lran显示文摘 | Esmaeili Dooki MR Rajabnia R Barari Sawadkohi R | 2014 | Caspian J Intern Med2014，5，1： | 1 |
| 6 | Feasibility study on the utiliza- tion as repair grouting of high flowable polymer-modified ce- ment mortar, adding high volume polyacrylic ester(PAE) 显示文摘 | Jeongyun Do Dookie Kim | 2008 | J Asian Architecture Building Eng2008，12，： | 1 |
| 7 | A comparison of mesalamine suspen- sion enema and oral sulfasalazine for treatment of active distal ulcera- tive colitis in adults 显示文摘 | Kam L Cohen H Dooky C | 1996 | Am J Gastroenterol1996，91，： | 1 |
| 8 | Prediction of compressive strength of self-compacting concrete using least square support vector machine and relevance vector machine显示文摘 | Bhairevi Ganesh Aiyer Dookie Kim Nithin Karingattikkal Pijush Samui P. Ramamohan Rao | 2014 | KSCE Journal of Civil Engineering2014，，6： | 1 |
| 9 | An improved application technique of the adaptive probabilistic neural network for predicting concrete strength 显示文摘 | Lee Jong Jae Kim Dookie Chang Seong Kyu | 2009 | Computational Materials Science2009，44，： | 1 |
| 10 | The role of TG2 in ECV304-related vasculogenic mimicry显示文摘 | Jones R A Wang Z Dookie S | 2013 | Amino Acids2013，44，1： | 1 |
| 11 | Periodic seismic performance evaluation of highway bridges using structural health monitoring system 显示文摘 | Yi Jin-Hak Kim Dookie Feng Maria Q | 2009 | Structural Engineering and Mechanics2009，31，5： | 1 |
| 12 | An Advanced Probabilistic Neural Network for the Design of Breakwater Armor Blocks显示文摘In this study,an advanced probabilistic neural network(APNN)method is proposed to reflect the global probability density function(PDF)by summing up the heterogeneous local PDF which is automatically determined in the individual standard deviation of variables.The APNN is applied to predict the stability number of armor blocks of breakwaters using the experimental data of van der Meer,and the estimated results of the APNN are compared with those of an empirical formula and a previous artificial neural network(ANN)model.The APNN shows better results in predicting the stability number of armor blocks of breakwater and it provided the promising probabilistic viewpoints by using the individual standard deviation in a variable. | Dookie KIM Dong Hyawn KIM Seongkyu CHANG Gil Lim YOON | 2007 | China Ocean Engineering2007，21，4： | 0 |
| 13 | 利用支持向量机和高斯过程回归测定水库诱发的地震(英文)显示文摘水库诱发地震震级(M)的预测是在地震工程中的一项重要任务。本文采用支持向量机(SVM)和高斯过程回归(GPR)模型根据水库的参数预测了水库诱发地震震级(M)。综合参数(E)和最大的水库深度(H)作为支持向量机和高斯过程回归模型的输入参数。我们给出一个方程确定水库诱发地震震级(M)。将本文开发的支持向量机和建立的高斯过程回归方法与人工神经网络(ANN)方法相比。结果表明,本文研发的支持向量机和高斯过程回归方法是预测水库诱发地震震级(M)的有效工具。 | Pijush Samui Dookie Kim | 2013 | Applied Geophysics2013，10，2： | 0 |
| 14 | 基于最小二乘支持向量机算法的小地锚抗拔承载力研究(英文)显示文摘目的:基于最小二乘支持向量机算法预测小地锚的抗拔承载力。方法:最小二乘支持向量机算法中的输入参数包括等效地锚直径,地锚埋置深度,平均顶椎阻力,平均椎套摩擦力以及安装工艺。使用现场试验的119组数据中的83组数据进行最小二乘支持向量机回归模型分析,并使用剩余的36组数据测试模型的拟合良好性;同时用敏感度分析研究每个输入参数的作用。结论:通过与人工神经网络模型的对比,发现最小二乘支持向量机的性能表现优异。 | Pijush SAMUI Dookie KIM Bhairevi G.AIYER | 2015 | Journal of Zhejiang University-Science A(Applied Physics & Engineering)2015，16，4： | 0 |
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