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이경환(KyeongHwan Lee),심규진(KyuJin Shim),악바르 완다 알리(Wanda Ali Akbar),정한식(HanShik Chung),정효민(HyoMin Jeong) 대한기계학회 2006 대한기계학회 춘추학술대회 Vol.2006 No.11
Nowadays, study about hydrogen fuel which consist of hydrogen extraction and reforming processes, fuel cell equipment, and receptacle are flourishing allover the world. Currently, Korea hydrogen station is still underdeveloping. And also the most important part which is hydrogen compressor has not been developed. Snubber is one of the important parts in hydrogen compressing system. It is installed before and after reciprocating hydrogen compressor. Snubber has two functions. One is making down pulsation waveform. Because pressure hydrogen gas where is after passing through reciprocation compressor part has high pulsation waveform, so this waveform has to decline. And the other function is precipitating alien substances to outside. Normally, even if 99.99% hydrogen gas is still containing alien substance. Buffer is set up inside snubber and the waveform will hit buffer. This snubber study uses CFD.
Modified screening-based Kriging method with cross validation and application to engineering design
Kang, Kyeonghwan,Qin, Caiyan,Lee, Bongjae,Lee, Ikjin Butterworths [etc.] 2019 Applied mathematical modelling Vol.70 No.-
<P><B>Abstract</B></P> <P>In this paper, a basis screening Kriging method using cross validation error is proposed to alleviate computational burden of the dynamic Kriging while maintaining its accuracy. Metamodeling is widely used for design optimization of complex engineering applications where considerable computation time is required. The Kriging method is one of popular metamodeling methods due to its accuracy and efficiency. There have been many attempts to improve accuracy of the Kriging method, and the dynamic Kriging method using cross-validation error, which selects adequate basis functions to best describe the mean structure of a response using a genetic algorithm, achieves outstanding performance in terms of accuracy. However, despite its accuracy, the dynamic Kriging requires very large amounts of computation because of the genetic algorithm and no limitation for order of basis functions. In the proposed method, a basis function set is determined by screening each basis function instead of using the genetic algorithm, which has advantages in computation for high dimensional metamodels or repeated metamodel generation. Numerical studies with four mathematical examples and two engineering applications verify that the proposed basis screening Kriging significantly reduces computation time with similar accuracy as the dynamic Kriging.</P> <P><B>Highlights</B></P> <P> <UL> <LI> Provides a illustrative study and discussion on the weaknesses of the dynamic Kriging method using cross validation error. </LI> <LI> Proposes improved Kriging method using screening procedure in terms of computational efficiency, without sacrificing accuracy. </LI> <LI> Performs design optimization of two engineering models using the proposed Kriging method to verify efficiency improvement. </LI> </UL> </P>
Patent Trend of Unmanned and Automated Agricultural Production - Open Field Operation -
Kim, YongJoo,Chung, SunOk,Lee, ChoongHan,Lee, DaeHyun,Lee, KyeongHwan Korean Society of Food and Agricultural Informatio 2014 Agribusiness and Information Management Vol.6 No.1
This study was conducted to determine the major patent and analyze the patent trend of unmanned and automated agricultural production for the open field operation. As a result of conducting a search for patent applications related to these technologies, 1,080 valid patents were selected by evaluating the relevance of the patents and removing noise patents. As a result of the country-based analysis using the selected valid patents, it was found out that the largest number of patent applications were filed in the United States with 541 cases, followed by Japan with 326 cases, the European Union with 128 cases, and Korea with 85 cases. Upon classifying the valid patents into core technology, the path generation and tracking technology accounts for 33% with 353 cases; the implementing control with environmental condition technology accounts for 22% with 236 cases; the robot design technology accounts for 21% with 228 cases; the plant and environment sensing technology accounts for 19% with 206 cases; the yield and quality monitoring technology accounts for 5% with 58 cases. Finally, 10 core patents were selected by performing a patent index evaluation. The United States registered all of the 10 core patents. The results showed that Korea falls behind in the open field-related unmanned and automated agricultural production, compared to other developed agricultural countries.
Patent Trend of Unmanned and Automated Agricultural Production : Open Field Operation
YongJoo Kim,SunOk Chung,ChoongHan Lee,DaeHyun Lee,KyeongHwan Lee 한국농식품정보과학회 2014 Agribusiness and Information Management Vol.6 No.1
This study was conducted to determine the major patent and analyze the patent trend of unmanned and automated agricultural production for the open field operation. As a result of conducting a search for patent applications related to these technologies, 1,080 valid patents were selected by evaluating the relevance of the patents and removing noise patents. As a result of the country-based analysis using the selected valid patents, it was found out that the largest number of patent applications were filed in the United States with 541 cases, followed by Japan with 326 cases, the European Union with 128 cases, and Korea with 85 cases. Upon classifying the valid patents into core technology, the path generation and tracking technology accounts for 33% with 353 cases; the implementing control with environmental condition technology accounts for 22% with 236 cases; the robot design technology accounts for 21% with 228 cases; the plant and environment sensing technology accounts for 19% with 206 cases; the yield and quality monitoring technology accounts for 5% with 58 cases. Finally, 10 core patents were selected by performing a patent index evaluation. The United States registered all of the 10 core patents. The results showed that Korea falls behind in the open field-related unmanned and automated agricultural production, compared to other developed agricultural countries.
Basis screening Kriging 기법을 이용한 효율적인 메타모델링 기법 및 스티어링 컬럼 설계
강경환(Kyeonghwan Kang),이익진(Ikjin Lee) 대한기계학회 2015 대한기계학회 춘추학술대회 Vol.2015 No.11
Metamodeling can be used for design optimization of engineering problems which need significant computational cost. Among the metamodeling methods, Kriging method is one of popular metamodeling methods for treating CAE result because it is based on interpolation method and has the capability to deal with highly nonlinear performance function. There have been a lot of research to improve the Kriging method, and the dynamic Kriging using cross validation error gives good performance in terms of accuracy because it selects adequate basis functions to construct a mean structure of a response using the genetic algorithm and cross validation error. Despite its accuracy, the dynamic Kriging using cross validation error (CVE) requires severe computational time and it could give bad estimation result occasionally because a fitness function of the genetic algorithm includes cross validation error calculation and inaccurate correlation parameter algorithm. In this paper, basis screening Kriging method is proposed to select basis functions and the maximum polynomial order using CVE in order to prevent overfitting and alleviate the computational burden. Numerical study and steering column design example is used to verify that the accuracy of the proposed method is similar to the accuracy of the dynamic Kriging but the computation time of the proposed method decreased compared to the dynamic Kriging using CVE.
강경환(Kyeonghwan Kang),이익진(Ikjin Lee) 대한기계학회 2014 대한기계학회 춘추학술대회 Vol.2014 No.11
Metamodeling has been used for design optimization of large-scale engineering problems. Kriging method is one of popular methods due to its accuracy and efficiency. There have been many attempts to improve the accuracy of Kriging method: blind Kriging, dynamic Kriging, etc. These attempts select adequate basis functions to describe the mean structure of the response. However, blind Kriging cannot describe a highly non-linear trend function accurately. In addition, dynamic Kriging takes significant computational time as the number of samples increases due to genetic algorithm and mean value of cross-validation error. In this paper, the new method that selects basis functions using process variance changes and cross-validation(CV) is proposed. Numerical study verified that the proposed method reduces computational time without sacrificing its accuracy.