입방형 영역에서의 G-효율이 높은 Model-Robust 실험설계

박유진(You-Jin Park),이윤주(Yoon-Ju Yi) 대한산업공학회 2010 산업공학 Vol.23 No.2

The determination of a regression model is important in using statistical designs of experiments. Generally, the exact regression model is not known, and experimenters suppose that a certain model form will be fit. Then an experimental design suitable for that predetermined model form is selected and the experiment is conducted. However, the initially chosen regression model may not be correct, and this can result in undesirable statistical properties. We develop model-robust experimental designs that have stable prediction variance for a family of candidate regression models over a cuboidal region by using genetic algorithms and the desirability function method. We then compare the stability of prediction variance of model-robust experimental designs with those of the 3-level face centered cube. These model-robust experimental designs have moderately high G-efficiencies for all candidate models that the experimenter may potentially wish to fit, and outperform the cuboidal design for the second-order model. The G-efficiencies are provided for the model-robust experimental designs and the face centered cube.

피드백을 활용한 과학실험수업 모형의 개발

양희선,심규철,김현섭 한국현장과학교육학회 2016 현장과학교육 Vol.10 No.2

This study was performed to develop the new experimental instruction model for a improvement science experimental instruction as the form of inquiry experimental learning. The development of new model was based on the property of inquiry experimental learning, analysis on the problems in school experimental instruction, the effect of collaborative learning and guided inquiry learning, and analysis on the previous studies on the importance of feedback process. The developed model based on these steps is composed of ‘Engagement (problem recognition step)’ and ‘DEAR (experiment performance and analysis step)’ steps. DEAR stands for Design, Experiment, Analysis, and Reflect. Therefore, the developed experiment instructional model was named as ‘E-DEAR model’. E-DEAR model is an instructional model for scientific experiment emphasizing on the feedback process. The model applies two feedback; collaborative feedback and guided feedback. The collaborative feedback is the inquiry activity of new form, which learn by himself/herself through the feedback with other students. Contrarily, the guided feedback is the interaction between teachers and students based on the inquiry instruction activity including the guided feedback by teachers. The both of feedback processes are conducted in each steps of new model to guide and promote students performing inquiry learning by themselves. Especially, E-DEAR model makes a learner record learning content in learning activity note by himself/herself through collaborative feedback process, which allows a feedback suitable to learner's level. Through this process, the insufficient learning content can be supplemented using the guided feedback. We have also investigated the recognition of student for the E-DEAR model after preliminary application. As a result, most student gave a positive answer all questions. Therefore it is expected that the E-DEAR model will have significant effect on students’ science experimental learning. 본 연구에서는 과학과 실험수업을 탐구적 실험학습 형태로 개선하기 위해 새로운 실험수업모형을 개발하였다. 모형의 개발은 탐구적 실험학습의 특성, 현장 실험수업의 문제점 분석, 협동학습과 안내된 탐구수업의 효과 그리고 피드백의 중요성에 관한 선행연구 자료의 분석을 통해 이루어졌다. 개발된실험수업모형은 문제인식 및 가설설정 과정인 ‘참여단계(Engagement)’와 실험수행 및 해석단계인 실험설계(Design), 실험수행(Experiment), 자료해석(Analysis), 반성(Reflect)의 하위단계로 구성되어, ‘E-DEAR 모형’이라고 명명하였다. E-DEAR 모형은 피드백 활동이 강조된 과학 실험학습 모형이다. 모형에서 활용된 피드백은 크게 협동적 피드백과 안내된 피드백으로 구분된다. 협동적 피드백은 협동학습의 상호작용에 피드백 요소를 더하여 단순한학생 상호간의 활동이 아니라 동료와의 피드백 과정을 통해 스스로 학습해 나가는 새로운 형태의 탐구적 활동이다. 반면에 안내된 피드백은 안내된탐구수업 활동에 교사에 의한 피드백이 더해진 교사와 학생간의 상호작용이다. 이러한 두 가지 피드백은 모형의 각 단계에서 모두 이루어지며 학생들이스스로 탐구학습을 할 수 있도록 안내하고 촉진하는 역할을 하게 된다. 특히, E-DEAR 모형은 협동적 피드백 과정을 통해 학습자가 수정한 학습내용을활동지에 기록하여 자신의 수준에 맞게 피드백이 이루어지도록 하고, 부족한 학습내용은 안내된 피드백에 의하여 보충할 수 있도록 구성되어 있다. 개발된 E-DEAR 모형을 시범 적용한 후 모형에 대한 인식을 조사한 결과, 대부분의 학생들이 모든 문항에 대해 긍정적인 반응을 나타내어 본 모형이학생들의 탐구적 실험학습에 효과적인 영향을 미칠 것으로 예상되었다.

농어촌 체험 고객 만족에 영향을 미치는 요인

최양애,정병규 사단법인 한국벤처혁신학회 2019 벤처혁신연구 Vol.2 No.2

The purpose of this study is to explore the factors affecting rural experience by applying the unified push-pull-mooring model. The theoretical model is an unified PPM model that introduces new variables based on PPM. The pull factor of the newly introduced variables were reconstructed based on the Schmitt’s Experience model and ServQual model. The hypothesis is set as follows. The push factor will have a negative effect on experience satisfaction and the pull factor(experience attributes, service quality)will have a positive effect on experience satisfaction. Also, mooring factors will have a negative effect on experience satisfaction. The research model of this study was tested by structural equation model based on 314 effective questionnaire data. Service quality had a positive effect on experience satisfaction. Mooring factors have a negative effect on experience satisfaction. Push factor and experience attributes factor were analyzed to have a no significance effect on experience satisfaction. These results theoretically test that the mooring factors also have an important effect on the experience satisfaction in the rural experience. Based on the Schmitt’s Experience model and ServQual model introduced as a pull factor, the proposed unified PPM model proved to be a useful analysis framework. In practice, it was able to provide implications on what factors should be strategically and marketingly focused to activate the 6th industry experience. 본 연구의 목적은 농어촌 체험에 영향을 미치는 요인을 통합된 PPM모델(unified push-pull-mooring model)을 적용하여 탐색하는 것이다. 이론적인 모델은 PPM을 근간으로 하여 새로운 변수들을 도입한 통합된 PPM모델이다. 새롭게 도입된 변수 중 pull 요인은 체험이론과 ServQual 모형을 바탕으로 재구성하였다. 종속변수는 고객 만족을 설정하였다. 가설은 다음과 같이 설정하였다. Push 요인은 체험 만족에 부(-)의 영향을 미치고, Pull 요인인 체험요소와 체험품질은 체험 만족에 정(+)의 영향을 미칠 것이다. 또한, mooring 요인은 체험 만족에 부(-)의 영향을 미칠 것이다. 본 연구의 연구 모형을 314개 설문데이터를 기반으로 하여 구조방정식으로 검정하였다. 연구 결과 Pull 요인인 체험품질은 체험 만족에 정(+)의 영향을 미쳤다. Mooring 요인은 체험의도에 부(-)의 영향을 미치는 것으로 나타났다. 하지만, push 요인과 체험 만족 간, 체험요소와 체험 만족 간에는 유의한 영향 관계가 검정되지 않았다. 이러한 연구 결과는 이론적으로는 농어촌 체험에 있어서 기존의 pull, push 요인 위주의 분석에서 나아가 심리적인 mooring 요인도 체험에 중요한 영향을 미친다는 것을 검정하였다. Pull 요인으로 도입된 체험요소와 체험품질을 바탕으로 제안된 통합된 PPM모델이 유용한 분석의 틀이 될 수 있음을 검정하였다. 실무적으로는 농어촌 체험을 활성화시키기 위해 어떠한 요소에 전략적으로나 마케팅적으로 집중해야 하는지에 대한 시사점을 제공할 수 있었다.

Modelling of Fault Deformation Induced by Fluid Injection using Hydro-Mechanical Coupled 3D Particle Flow Code: DECOVALEX-2019 Task B

Jeoung Seok Yoon(윤정석),Jian Zhou 한국암반공학회 2020 터널과지하공간 Vol.30 No.4

본 수치해석연구에서는 국제공동연구프로젝트 DECOVALEX2019의 Task B의 일환으로 PFC3D를 기반으로한 수리역학연계모델을 개발하여 스위스 Mont Terri 지하연구시설에서 수행된 단층의 유체주입으로 인한 슬립시험을 모사하였다. 이를통해, 개발한 PFC3D 수리역학연계모델이 가진 한계점과 향후 보완할 점을 검토하고자 하였다. PFC3D를 기반으로한 3차원 입자결합모델 내 공극-유동통로모델을 생성하였으며 이를 사용하여 Mont Terri Step 2 단층내 유체주입실험을 모사하였다. 모델링결과 단층대를 따라 주입유체의 유동에 의한 단층대의 변형을 확인하였지만, 관측정에서의 시간에 따른 수압변화는 현장측정치와 부분적으로 일치하는 경향을 확인하였다. 현장측정 관측수압은 초기 유체주입 압력증가에 거의 변화를 보이지 않고 주입수압이 최대치에 도달할때쯤 급격한 증가를 보이는반면, 모델링에서는 주입압력이 증가함에 따라 관측수압도 부드럽게 증가하는 경향을 보였다. 이러한 부분적으로 일치하는 결과의 원인으로는 Mont Terri 현장의 단층을 모사하는 방법에 기인하는 것으로 판단하다. PFC3D에서는 단층을 손상대와 코어균열의 조합으로 모사하였고 단층대의 두께가 약 2 m로 주입유체가 단층대를 통해 유동하도록 모사하였기에 현장에서의 주입유체의 단층내 유동보다 그 유동범위가 크게 모사되었다고 판단한다. 또한, 현장단층에서와 같이 단층내부에 존재하는 충진물질로 인해 단층내 수리유동이 제한되어 국부적으로 과잉공급수압이 형성될 수 있는 기재를 모사하지 못한 점 또한 모델링 결과와 현장측정결과가 부분적으로 일치하는 원인일 수 있다. 단층변형의 경우는 모델링결과와 현장측정결과 유사한 수준으로 일치하는 결과를 확인하였다. 수치모델을 변형하여 단층대의 두께를 감소시키고 단층내 충진 물질의 비균질적인분포를 모사할 수 있는 방법론에 대한 후속 연구를 통해 PFC3D 수리역학연계모델의 유체주입으로 인한 단층활성화 연구로의 적용성을 향상시키는 것을 제안하고 한다. This study presents an application of hydro-mechanical coupled Particle Flow Code 3D (PFC3D) to simulation of fluid injection induced fault slip experiment conducted in Mont Terri Switzerland as a part of a task in an international research project DECOVALEX-2019. We also aimed as identifying the current limitations of the modelling method and issues for further development. A fluid flow algorithm was developed and implemented in a 3D pore-pipe network model in a 3D bonded particle assembly using PFC3D v5, and was applied to Mont Terri Step 2 minor fault activation experiment. The simulated results showed that the injected fluid migrates through the permeable fault zone and induces fault deformation, demonstrating a full hydro-mechanical coupled behavior. The simulated results were, however, partially matching with the field measurement. The simulated pressure build-up at the monitoring location showed linear and progressive increase, whereas the field measurement showed an abrupt increase associated with the fault slip We conclude that such difference between the modelling and the field test is due to the structure of the fault in the model which was represented as a combination of damage zone and core fractures. The modelled fault is likely larger in size than the real fault in Mont Terri site. Therefore, the modelled fault allows several path ways of fluid flow from the injection location to the pressure monitoring location, leading to smooth pressure build-up at the monitoring location while the injection pressure increases, and an early start of pressure decay even before the injection pressure reaches the maximum. We also conclude that the clay filling in the real fault could have acted as a fluid barrier which may have resulted in formation of fluid over-pressurization locally in the fault. Unlike the pressure result, the simulated fault deformations were matching with the field measurements. A better way of modelling a heterogeneous clay-filled fault structure with a narrow zone should be studied further to improve the applicability of the modelling method to fluid injection induced fault activation.

크리깅 메타모델의 전역모델과 상관계수 선정 방법

조수길(Su Kil Cho),변현석(Hyun-suk Byun),이태희(Tae Hee Lee) 대한기계학회 2009 大韓機械學會論文集A Vol.33 No.8

Design analysis and computer experiments (DACE) model is widely used to express efficiently nonlinear responses in the field of engineering design. As a DACE model, kriging model can approximately replace a simulation model that is very expensive or highly nonlinear. The kriging model is composed of the summation of a global model and a local model representing deviation from the global model. The local model is determined by correlation coefficient with the pre-sampled points, where the accuracy and robustness of the kriging model depends on the selection of proper correlation coefficients. Therefore, to achieve the robust kriging model, the range of the correlation coefficients is explored with respect to the degrees of the global model. Based on this study we propose the proper orders of the global model and range of parameters to make accurate and robust kriging model.

구조실험정보를 위한 데이터 모델의 개발 및 구현 과정에 대한 분석

이창호(Lee Chang-Ho) 대한건축학회 2010 大韓建築學會論文集 : 構造系 Vol.26 No.7

The data models for the structural experiments organize formally the information involved in the structural experiments, and the formally organized information is used for implementing the computer systems. Previous research on the data models has provided various data models for their own application fields of the structural experiments, but their development methods has not been carefully reviewed and discussed. This paper analyzes the development and implementation procedure of the data models for structural experiments including the Lehigh Model for large-scale and hybrid structural experiments, the NEES data model for general categories of experiments, and the KOCED data model for distributed and shared experiments. Based on the analysis, some noticeable suggestions are given to be considered for developing the comprehensive data models for the structural experiments. The domain of the data models should be clearly defined at the initial stage of the development procedure. The categories and the levels of the information need to be decided considering the characteristics of the structural experiments. The most significant part of a data model is to be formulated first because the initial formulation affects the rest of the development procedure and the data model evolves during the development procedure.

구조실험정보를 위한 데이터 모델의 특성평가 요소

이창호(Lee Chang-Ho) 대한건축학회 2010 大韓建築學會論文集 : 構造系 Vol.26 No.8

The information involved in the structural experiments can be formally organized using the date models before the computer systems are implemented. A number of data models have been developed by the previous research efforts, such as the NEES data model for general information of structural experiments and the Lehigh Model for the large-scale and hybrid structural experiments. The comparisons and evaluations for the data models have been made only by the descriptive way, not by the numerical way. This paper proposes some numerical criteria for evaluating characteristics of data models for structural experiments. The criteria for the classes in a data model includes the total number of classes, the number of attributes in class, and the average number of attributes in class to describe the size and volume of the data model. The criteria for the objects includes the ratio of objects to classes, the ratio of attribute value existence in class, and the number of selections for value to describe the use of the data models for a specific project and to describe the complexity of the paths for specific information in the data model. These criteria are applied for the Lehigh model and the NEES data model, and the numerical values for the criteria are used for describing the characteristics of the two date models.

확장된 PPM 모델을 적용한 6차산업 체험의도에 영향을 미치는 요인에 관한 연구

최양애,정병규 한국유통경영학회 2019 유통경영학회지 Vol.22 No.4

The purpose of this study is to explore the factors affecting the 6th industry experience by applying the extended PPM model. The theoretical model is an extended PPM model that introduces new variables based on PPM. The newly introduced variables are the cognitive experience, emotional experience, and social experience that are reconstructed based on Schmitt's experience theory and trust as a mediating variable. The hypothesis was set as follows. The push factor will have a negative(-) effect on intention to experience, and the pull factor that are the cognitive experience, the emotional experience, and the social experience will have a positive(+) influence on the intention to experience. Mooring factors will have a negative(-) effect on intention to experience. Trust will play a mediating role between these variables. The research was based on 314 questionnaire data and tested by structural equation model. As a result of the research, it was found that the factors that have the greatest effect on the intention to experience were emotional experience. Cognitive experience and emotional experience had positive(+) effects on experience intention. Push and mooring factors have negative(-) effects on experience intention. On the other hand, it was not confirmed that social experience has a significant influence on experience intention. Trust was found to play a mediating role between cognitive experience, emotional experience, social experience and experience intention. However, the mediating effect between push factors, mooring factors and experience intention was not supported. The results of this study are theoretically confirmed that the push factor and the mooring factor have an important influence on the experience intention in addition to the analysis of the existing pull factor in the 6th industry experience and the extended PPM model proposed in this study is useful framework of analysis. In practical terms, it could provide implications for what factors should be strategically and marketingly focused to activate the 6th industry experience. 본 연구의 목적은 6차 산업 체험에 영향을 미치는 요인을 확장된 PPM모델을 적용하여 탐색하는 것이다. 이론적인 모델은 PPM을 근간으로 하여 새로운 변수들을 도입한 확장된 PPM모델이다. 새롭게 도입된 변수는 매개변수로 신뢰성(trust)과 pull요인에 Schmitt의 체험이론을 바탕으로 재구성한 인지적 요인, 정서적 요인, 사회적 요인이다. 가설은 다음과 같이 설정하였다. Push 요인은 체험의도에 부(-)의 영향을 미치고, pull요인인 인지적 요인, 정서적 요인, 사회적 요인은 체험의도에 정(+)의 영향을 미칠 것이다. 또한, mooring 요인은 체험의도에 부(-)의 영향을 미칠 것이다. 신뢰성은 이들 변수 간에 매개역할을 할 것이다. 본 연구의 연구 모형을 314개 설문데이터를 기반으로 하여 구조방정식으로 검정하였다. 연구 결과 체험의도에 영향을 가장 크게 미치는 요인은 정서적 요인으로 밝혀졌다. 인지적 요인, 정서적 요인은 체험의도에 정(+)의 영향을 미쳤다. Push요인과 mooring요인은 체험의도에 부(-)의 영향을 미치는 것으로 나타났다. 반면, 사회적 요인은 체험의도에 유의한 영향 관계가 있음이 검정되지 않았다. 매개변수로 투입된 신뢰성은 인지적 요인, 정서적 요인, 사회적 요인과 체험 의도간 부분 매개역할을 하는 것으로 나타났다. 하지만 Push요인 및 mooring 요인과 체험의도 간에는 매개효과가 검정되지 않았다. 이러한 연구결과는 이론적으로는 6차산업 체험에 있어서 기존의 pull요인 위주의 분석에서 나아가 push요인과 mooring 요인도 체험 의도에 중요한 영향을 미친다는것을 검정하였고, 본 연구에서 제안된 확장된 PPM모델이 유용한 분석의 틀이 될 수 있음을 검정하였다. 실무적으로는 6차산업 체험을 활성화시키기 위해 어떠한 요소에 전략적으로나 마케팅적으로 집중해야 하는지에 대한 시사점을 제공할 수 있었다.

확률적 머신러닝 모델기반의 리튬이온배터리 파라미터 추정 알고리즘

김민호(Minho Kim),송민석(Minseok Song),임정택(Jeongtaek Lim),함경선(Kyung Sun Ham),이도헌(DOHEON LEE),김태형(Taehyoung Kim) 한국에너지학회 2024 에너지공학 Vol.33 No.1

In this study, a new lithium-ion battery performance degradation model and a stochastic machine learning model-based lithium-ion battery parameter estimation method were proposed and verified through actual battery degradation cycle experiment data. The proposed parameter estimation method based on a stochastic machine learning model requires less battery model operation time compared to other methods, enabling efficient parameter estimation. The lithium-ion battery performance degradation model is an equivalent circuit-based model, but it reflects various electrochemical phenomena, including side reactions on the surface of the anode active material, including the formation of a solid electrolyte interphase (SEI) layer, the loss of positive electrode active material due to mechanical stress-induced fatigue failure is included, and the corresponding decrease in the amount of cyclable lithium. In the proposed method of estimating the parameters of a lithium-ion battery model, a probabilistic machine learning model that can estimate battery model parameters from sensible data such as voltage and current is developed and used to generate virtual experiment data. We proposed a technique for learning and finding optimal battery model parameters based on the learned model. The developed performance degradation model and parameter estimation method were verified based on actual experimental data. Since it is impossible to observe the inside of the battery, correct answers to the battery parameters cannot be obtained, so the model and parameter estimation algorithm are indirectly verified through errors of voltage and temperature. As a result of the verification, the errors in voltage and temperature were found to be 0.676% and 0.207%, respectively.

실험계획법을 활용한 풍동실험의 효율성 및 생산성 향상에 관한 연구

고현준,박성연,김재우,권기범 한국항공우주학회 2015 한국항공우주학회 학술발표회 논문집 Vol.2015 No.11

풍동실험에 소요되는 시간과 비용을 절감하고자 적은 수의 풍동실험 결과를 가지고 실험계획법(Design of Experiment, DOE)을 이용하여 생성한 공력반응모델이 기존의 OFAT(One Factor At a Time) 방식의 실험을 통해 획득되는 공력계수 예측에 적합한지를 판단하고 이러한 모델의 활용 가능성에 대한 연구를 수행하였다. 1차적으로 받음각, 옆미끄럼각, 유속을 실험변수로 설정하여 실험하고, Effect Screening Test를 통해 유속을 변수에서 제외하였다. 실험계획법으로 라틴정방설계법(Latin Hypercube Design, LHD)과 중심합성설계법(Central Composite Design)을 사용하여 실험을 계획하였고 반응모델로는 반응표면모델과 인공신경망모델이 고려되었으나 검증 결과 인공신경망모델의 정확성이 더 높다고 판단하여 인공신경망 모델을 채택하였다. 기존의 OFAT 방식으로 수행한 풍동실험으로 얻은 T-50 축소모형의 데이터와 인공신경망모델의 예측값을 비교하여 해당 모델이 공력계수 예측에 적합한지 판단하고 실험계획법이 풍동실험의 효율성과 생산성 향상에 기여할 수 있는 가능성을 분석하였다. A study is conducted to decide suitability of prediction model for estimating aerodynamic coefficients created by using DOE(Design Of Experiment) to reduce time and cost in wind tunnel tests. First, angle of attack, side slip angle, and flow velocity are selected as test variables and flow velocity is excluded after effect screening test. LHD(Latin Hypercube Design) and CCD(Central Composite Design) are used for designing the experiment. In order to create the metamodel, NN(Neural Network) model is chosen because it is more accurate than RSM(Response Surface Model) in prediction accuracy. The test data of T-50 5% model acquired by usual OFAT(One Factor At a Time) is compared with the prediction values estimated by NN prediction model. The adequacy and applicability of the model is analyzed to show the possibility of improvement in efficiency and productivity of wind tunnel tests using DOE.