Discretization approach

학위논문(박사)--서울대학교 대학원 :공과대학 화학생물공학부(에너지환경 화학융합기술전공),2019. 8. 이원보.In recent years, many researchers in chemical engineering have made great efforts to develop mathematical models on the theoretical side that are consistent with experimental results. Despite these efforts, however, establishing models for a system with complex phenomena such as multiphase flow or stirred reactors is still considered to be a challenge. In the meantime, an increase in computational efficiency and stability in various numerical methods has allowed us to correctly solve and analyze the system based on the fundamental equations. This leads to the need for a mathematical model to accurately predict the behavior of systems in which there is interdependence among the internal elements. A methodology for building a model based on equations that represent fundamental phenomena can lower technical barriers in system analysis. In this thesis, we propose three mathematical models validated from laboratory or pilot-scale experiments. First, an apparatus for vaporizing liquid natural gas is surrounded with a frost layer formed on the surface during operation, and performance of the apparatus is gradually deteriorated due to the adiabatic effect. Because the system uses ambient air as a heat sink, it is necessary to consider the phase transition and mass transfer of water vapor, and natural gas in the air in order to understand the fluctuation of system characteristics. The model predicts the experimental data of a pilot-scale vaporizer within a mean absolute error of 5.5 %. In addition, we suggest the robust design methodology and optimal design which is able to maintain the efficiency under the weather conditions for a year. Two or more data analysis techniques including discrete waveform transformation and k-means clustering are used to extract features that can represent time series data. Under the settings, the performance in the optimized desgin is improved by 22.92 percentage points compared to that in the conventional system. In the second system, the continuous tubular crystallization reactor has advantages in terms of production capacity and scale-up compared with the conventional batch reactor. However, the tubular system requires a well-designed control system to maintain its stability and durability, and thus; there is a great deal of demand for the mathematical model of this system. We were able to estimate crystal size distribution by considering the population balance model simultaneously with several heat exchanger models. The model constructed based on the first principle reaction scheme successfully predicted the results from the full-factorial experiment. The experiments were conducted with LAM (L-asparagine monohydrate) solution. In the prediction, the average crystal length and standard deviation were within 20% of the results of an experiment where the crystals were not iteratively dissolved in the liquid but maintained a low-level supersaturation. Furthermore, to confirm the controllability of the crystal size distribution in the system, we replaced the LAM solution with HEWL (Hen-egg white lysozyme) solution. Finally, we propose a multi-compartment model to predict the behavior of a high-pressure autoclave reactor for polymer production. In order to simulate a complex polymer synthesis mechanism, the rotation effect of impellers in the reactor on polymerization and the influence caused by polymerization heat were sequentially evaluated. As a result, This model turned out to be able to predict the physical properties of the polymers produced in an industrial-scale reactor within 7% accuracy. In this thesis, all three systems are distributed parameter systems which can be expressed as partial differential equations for time and space. To construct a high order model, the system was interpreted based on discretization approach under minimal assumptions. This methodology can be applied not only to the systems suggested in this thesis but also to those consisting of interpdependent variables. I hope that this thesis provides guidance for further researches of chemical engineering in nearby future.최근에 몇 년에 걸쳐서 많은 연구자들이 이론을 기반으로 실험 결과와 일치하는 수학 모델을 개발하고자 많은 노력을 기울여 왔다. 하지만 이런 노력에도 불구하고 다상 흐름 혹은 교반 반응기와 같은 복잡한 현상을 내포한 시스템을 위한 모델을 수립하는 것은 여전히 화학 공학 분야에서 쉽지 않은 일로 여겨진다. 이 와중에 다양한 수치적 방법에서의 계산 효율의 증가와 안정성의 향상은 기본방정식에 기초한 시스템을 정확하게 해결하고 분석할 수 있게 해주었다. 이로 인하여 내부 요소들 간의 상호 의존성이 존재하는 시스템의 거동을 정확하게 예측하기 위한 수학적 모델의 필요성이 부각되었다. 기본 현상들을 표현할 수 있는 방정식들을 기반으로 모델을 구축하기 위한 방법론은 시스템 해석에 있어서 기술적 장벽을 낮출 수 있다. 이 학위 논문에서 우리는 실험실 또는 파일럿 규모의 실험으로부터 입증된 세 가지 수학적 모델을 제안한다. 첫 번째로, 공기를 사용하여 액상의 천연가스를 기화시키는 장치는 운전 도중에 기화기 표면에 서리 층이 형성되고 그로 인한 단열 효과로 장비의 성능이 서서히 저하된다. 시스템은 주변 공기를 열 흡수원으로 사용하기 때문에 시스템 특성의 변동을 파악하기 위해서는 공기 중 수증기 및 천연 가스의 상전이 및 전달 현상을 동시에 고려하여야 한다. 제시된 수학적 모델에 의해 예측한 결과는 파일럿 규모 기화기로부터 얻은 실험 데이터와 5.5% 평균 절대 오차를 보였다. 이에 더하여, 앞에서 제시한 기화기 모델을 이용하여 1년 동안의 기상 조건에서 운전 효율을 유지하면서 지속 운전이 가능한 기화기의 설계 방법과 결과를 제안하였다. 이산 파형 변환과 k-평균 군집화를 포함하는 두 가지 이상의 데이터 분석 기법을 사용하여 시계열 데이터를 대표할 수 있는 특징을 추출한다. 추출된 특징 아래에서 최적화된 디자인은 기존 제시된 안에 비해 22.92% 만큼 향상된 성능을 보여주었다. 두 번째 시스템은 신 제약 기술 공정인 연속 관형 결정화 반응기는 기존에 널리 쓰이던 회분식 반응기에 비하여 생산 속도 및 스케일 업 측면에서 장점이 많다. 하지만 제어기술이 기반이 되어야한다는 점에 있어서 그 도입이 늦어졌고 이에 따라 자연스럽게 개발된 모델 또한 전무하다. 우리는 이 장치에서 결정 크기 분포를 추산하기 위한 인구 균형 모델을 열 교환 모델과 동시에 고려하여 결정 크기 분포를 추산할 수 있었다. 제 1원리 결정 반응식을 기반으로 구축된 모델은 완전 요인 배치법을 기반으로 실험된 데이터를 성공적으로 예측하였다. 결정이 액상에 용해되지 않으면서 낮은 수준의 과포화 상태를 유지한 실험에 대해서는 평균 결정 길이와 표준편차가 실험 결과와 20% 이내의 오차를 보였다. 앞에서 모델의 검증에 사용된 데이터가 LAM (L-아스파라긴 일 수화물)용액으로부터 얻어진 것이었다면 이후에는 HEWL (달걀 흰자 리소자임)를 사용하여 제품의 결정 크기 분포의 조절 가능성을 보였다. 마지막으로 폴리머 생산을 위한 고압 오토클레이브 반응기의 거동을 예측하기 위한 다중 구획 모델을 제안하였다. 복잡한 고분자 합성 메커니즘을 모사하기 위하여 반응기 내 임펠러의 회전이 중합에 미치는 효과와 중합 열로 인한 영향력을 순차적으로 평가하였다. 제안된 모델은 3D 구조를 가진 산업화된 반응기에서 생산된 두 가지 고분자의 물성을 7%이내 정확도로 예측할 수 있다. 본 학위논문에서는 다루는 시스템은 모두 분포 정수계 시스템으로 시간과 공간에 대하여 편미분방정식으로 표현할 수 있다. 고차 모델을 구축하기 위해 이산화 접근법을 기반으로 최소한의 가정 하에 시스템을 해석하였다. 이는 논문에 제시한 시스템 뿐만 아니라 시공간에서 예측 어려운 분포를 가지는 변수를 가진 모든 시스템에 대하여 적용이 가능하다. 이 논문이 앞으로 화학 공학 분야의 시스템을 해석하는 데 있어서 더 발전된 연구를 위한 지침서가 되기를 희망한다.Abstract i Contents iv List of Figures viii List of Tables xii Chapter 1 1 Introduction 1 1.1 Research motivation 1 1.2 Research objective 3 1.3 Outline of the thesis 4 1.4 Associated publications 9 Chapter 2 10 Distributed parameter system 10 2.1 Introduction 10 2.2 Modeling methods 11 2.3 Conclusion 16 Chapter 3 17 Modeling and design of pilot-scale ambient air vaporizer 17 3.1 Introduction 17 3.2 Modeling and analysis of frost growth in pilot-scale ambient air vaporizer 24 3.2.1 Ambient air vaporizer 24 3.2.2 Experimental measurement 27 3.2.3 Numerical model of the vaporizer 31 3.2.4 Result and discussion 43 3.3 Robust design of ambient air vaporizer based on time-series clustering 58 3.3.1 Background 58 3.3.2 Trend of time-series weather conditions 61 3.3.3 Optimization of AAV structures under time-series weather conditions 63 3.3.4 Results and discussion 76 3.4 Conclusion 93 3.4.1 Modeling and analysis of AAV system 93 3.4.2 Robust design of AAV system 95 Chapter 4 97 Tunable protein crystal size distribution via continuous crystallization 97 4.1 Introduction 97 4.2 Mathematical modeling and experimental verification of fully automated continuous slug-flow crystallizer 101 4.2.1 Experimental methods and equipment setup 101 4.2.2 Mathematical model of crystallizer 109 4.2.3 Results and discussion 118 4.3 Continuous crystallization of a protein: hen egg white lysozyme (HEWL) 132 4.3.1 Introduction 132 4.3.2 Experimental method 135 4.3.3 Results and discussion 145 4.4 Conclusion 164 4.4.1 Mathematical model of continuous crystallizer 164 4.4.2 Tunable continuous protein crystallization process 165 Chapter 5 167 Multi-compartment model of high-pressure autoclave reactor for polymer production: combined CFD mixing model and kinetics of polymerization 167 5.1 Introduction 167 5.2 Method 170 5.2.1 EVA autoclave reactor 170 5.2.2 Multi-compartment model of the autoclave reactor 173 5.2.3 CFD simulation of mixing effects in the autoclave reactor 175 5.2.4 Region-based dividing algorithm 178 5.2.5 Polymerization kinetic model 182 5.3 Results and discussion 191 5.4 Conclusion 203 5.5 Appendix 205 Chapter 6 210 Concluding Remarks 210 6.1 Summary of contributions 210 6.2 Future work 211 Appendix 214 Acknowledgment and collaboration declaration 214 Supplementary materials 217 Reference 227 Abstract in Korean (국문초록) 249Docto

A Framework to Develop Anomaly Detection/Fault Isolation Architecture Using System Engineering Principles

For critical systems, timely recognition of an anomalous condition immediately starts the evaluation process. For complex systems, isolating the fault to a component or subsystem results in corrective action sooner so that undesired consequences may be minimized. There are many unique anomaly detection and fault isolation capabilities available with innovative techniques to quickly discover an issue and identify the underlying problems. This research develops a framework to aid in the selection of appropriate anomaly detection and fault isolation technology to augment a given system. To optimize this process, the framework employs a model based systems engineering approach. Specifically, a SysML model is generated that enables a system-level evaluation of alternative detection and isolation techniques, and subsequently identifies the preferable application(s) from these technologies A case study is conducted on a cryogenic liquid hydrogen system that was used to fuel the Space Shuttles at the Kennedy Space Center, Florida (and will be used to fuel the next generation Space Launch System rocket). This system is operated remotely and supports time-critical and highly hazardous operations making it a good candidate to augment with this technology. As the process depicted by the framework down-selects to potential applications for consideration, these too are tested in their ability to achieve required goals

Muiltifunctional fuel additives for reduced jet particlate emissions

ReportUsing Government drawings, specifications, or other data included in this document for any purpose other than Government procurement does not in any way obligate the U.S. Government. The fact that the Government formulated or supplied the drawings, specifications, or other data does not license the holder or any other person or corporation; or convey any rights or permission to manufacture, use, or sell any patented invention that may relate to them

Chemical Characterization of African Biomass Burning Over the Southeast Atlantic Ocean.

M.S. Thesis. University of Hawaiʻi at Mānoa 2018

Data Requirements to Enable PHM for Liquid Hydrogen Storage Systems from a Risk Assessment Perspective

Quantitative Risk Assessment (QRA) aids the development of risk-informed safety codes and standards which are employed to reduce risk in a variety of complex technologies, such as hydrogen systems. Currently, the lack of reliability data limits the use of QRAs for fueling stations equipped with bulk liquid hydrogen storage systems. In turn, this hinders the ability to develop the necessary rigorous safety codes and standards to allow worldwide deployment of these stations. Prognostics and Health Management (PHM) and the analysis of condition-monitoring data emerge as an alternative to support risk assessment methods. Through the QRA-based analysis of a liquid hydrogen storage system, the core elements for the design of a data-driven PHM framework are addressed from a risk perspective. This work focuses on identifying the data collection requirements to strengthen current risk analyses and enable data-driven approaches to improve the safety and risk assessment of a liquid hydrogen fueling infrastructure

An unmanned aerial vehicle sampling platform for atmospheric water vapor isotopes in polar environments

Above polar ice sheets, atmospheric water vapor exchange occurs across the planetary boundary layer (PBL) and is an important mechanism in a number of processes that affect the surface mass balance of the ice sheets. Yet, this exchange is not well understood and has substantial implications for modeling and remote sensing of the polar hydrologic cycle. Efforts to characterize the exchange face substantial logistical challenges including the remoteness of ice sheet field camps, extreme weather conditions, low humidity and temperature that limit the effectiveness of instruments, and dangers associated with flying manned aircraft at low altitudes. Here, we present an unmanned aerial vehicle (UAV) sampling platform for operation in extreme polar environments that is capable of sampling atmospheric water vapor for subsequent measurement of water isotopes. This system was deployed to the East Greenland Ice-core Project (EastGRIP) camp in northeast Greenland during summer 2019. Four sampling flight missions were completed. With a suite of atmospheric measurements aboard the UAV (temperature, humidity, pressure, GPS) we determine the height of the PBL using online algorithms, allowing for strategic decision-making by the pilot to sample water isotopes above and below the PBL. Water isotope data were measured by a Picarro L2130-i instrument using flasks of atmospheric air collected within the nose cone of the UAV. The internal repeatability for δD and δ18O was 2.8 ‰ and 0.45 ‰, respectively, which we also compared to independent EastGRIP tower-isotope data. Based on these results, we demonstrate the efficacy of this new UAV-isotope platform and present improvements to be utilized in future polar field campaigns. The system is also designed to be readily adaptable to other fields of study, such as measurement of carbon cycle gases or remote sensing of ground conditions.publishedVersio

Experimental and Numerical Analysis of Ethanol Fueled HCCI Engine

Presently, the research on the homogeneous charge compression ignition (HCCI) engines has gained importance in the field of automotive power applications due to its superior efficiency and low emissions compared to the conventional internal combustion (IC) engines. In principle, the HCCI uses premixed lean homogeneous charge that auto-ignites volumetrically throughout the cylinder. The homogeneous mixture preparation is the main key to achieve high fuel economy and low exhaust emissions from the HCCI engines. In the recent past, different techniques to prepare homogeneous mixture have been explored. The major problem associated with the HCCI is to control the auto-ignition over wide range of engine operating conditions. The control strategies for the HCCI engines were also explored. This dissertation investigates the utilization of ethanol, a potential major contributor to the fuel economy of the future. Port fuel injection (PFI) strategy was used to prepare the homogeneous mixture external to the engine cylinder in a constant speed, single cylinder, four stroke air cooled engine which was operated on HCCI mode. Seven modules of work have been proposed and carried out in this research work to establish the results of using ethanol as a potential fuel in the HCCI engine. Ethanol has a low Cetane number and thus it cannot be auto-ignited easily. Therefore, intake air preheating was used to achieve auto-ignition temperatures. In the first module of work, the ethanol fueled HCCI engine was thermodynamically analysed to determine the operating domain. The minimum intake air temperature requirement to achieve auto-ignition and stable HCCI combustion was found to be 130 °C. Whereas, the knock limit of the engine limited the maximum intake air temperature of 170 °C. Therefore, the intake air temperature range was fixed between 130-170 °C for the ethanol fueled HCCI operation. In the second module of work, experiments were conducted with the variation of intake air temperature from 130-170 °C at a regular interval of 10 °C. It was found that, the increase in the intake air temperature advanced the combustion phase and decreased the exhaust gas temperature. At 170 °C, the maximum combustion efficiency and thermal efficiency were found to be 98.2% and 43% respectively. The NO emission and smoke emissionswere found to be below 11 ppm and 0.1% respectively throughout this study. From these results of high efficiency and low emissions from the HCCI engine, the following were determined using TOPSIS method. They are (i) choosing the best operating condition, and (ii) which input parameter has the greater influence on the HCCI output. In the third module of work, TOPSIS - a multi-criteria decision making technique was used to evaluate the optimum operating conditions. The optimal HCCI operating condition was found at 70% load and 170 °C charge temperature. The analysis of variance (ANOVA) test results revealed that, the charge temperature would be the most significant parameter followed by the engine load. The percentage contribution of charge temperature and load were63.04% and 27.89% respectively. In the fourth module of work, the GRNN algorithm was used to predict the output parameters of the HCCI engine. The network was trained, validated, and tested with the experimental data sets. Initially, the network was trained with the 60% of the experimental data sets. Further, the validation and testing of the network was done with each 20% data sets. The validation results predicted that, the output parameters those lie within 2% error. The results also showed that, the GRNN models would be advantageous for network simplicity and require less sparse data. The developed new tool efficiently predicted the relation between the input and output parameters. In the fifth module of work, the EGR was used to control the HCCI combustion. An optimum of 5% EGR was found to be optimum, further increase in the EGR caused increase in the hydrocarbon (HC) emissions. The maximum brake thermal efficiency of 45% was found for 170 °C charge temperature at 80% engine load. The NO emission and smoke emission were found to be below 10 ppm and 0.61% respectively. In the sixth module of work, a hybrid GRNN-PSO model was developed to optimize the ethanol-fueled HCCI engine based on the output performance and emission parameters. The GRNN network interpretive of the probability estimate such that it can predict the performance and emission parameters of HCCI engine within the range of input parameters. Since GRNN cannot optimize the solution, and hence swarm based adaptive mechanism was hybridized. A new fitness function was developed by considering the six engine output parameters. For the developed fitness function, constrained optimization criteria were implemented in four cases. The optimum HCCI engine operating conditions for the general criteria were found to be 170 °C charge temperature, 72% engine load, and 4% EGR. This model consumed about 60-75 ms for the HCCI engine optimization. In the last module of work, an external fuel vaporizer was used to prepare the ethanol fuel vapour and admitted into the HCCI engine. The maximum brake thermal efficiency of 46% was found for 170 °C charge temperature at 80% engine load. The NO emission and smoke emission were found to be below 5 ppm and 0.45% respectively. Overall, it is concluded that, the HCCI combustion of sole ethanol fuel is possible with the charge heating only. The high load limit of HCCI can be extended with ethanol fuel. High thermal efficiency and low emissions were possible with ethanol fueled HCCI to meet the current demand

Near-infrared light-controlled systems for gene transcription regulation, protein targeting and spectral multiplexing

Near-infrared (NIR, 740-780 nm) optogenetic systems are well-suited to spectral multiplexing with blue-light-controlled tools. Here, we present two protocols, one for regulation of gene transcription and another for control of protein localization, that use a NIR-responsive bacterial phytochrome BphP1-QPAS1 optogenetic pair. In the first protocol, cells are transfected with the optogenetic constructs for independently controlling gene transcription by NIR (BphP1-QPAS1) and blue (LightOn) light. The NIR and blue-light-controlled gene transcription systems show minimal spectral crosstalk and induce a 35- to 40-fold increase in reporter gene expression. In the second protocol, the BphP1-QPAS1 pair is combined with a light-oxygen-voltage-sensing (LOV) domain-based construct into a single optogenetic tool, termed iRIS. This dual-light-controllable protein localization tool allows tridirectional protein translocation among the cytoplasm, nucleus and plasma membrane. Both procedures can be performed within 3-5 d. Use of NIR light-controlled optogenetic systems should advance basic and biomedical research.Peer reviewe

Graphite lubrication mechanism under high mechanical load

Viele tribologische Extremanwendungen wie im Vakuum, in sauren Umgebungen, bei Hochtemperaturanwendungen oder unter hoher Last sind anspruchsvoll und führen oft zum Versagen herkömmlicher flüssiger Schmierstoffe wie Öle und Fette. Für diese Fälle stellen Festschmierstoffe wie Graphit eine exzellente Alternative dar. Trotz seiner frühen Entdeckung ist das Verständnis des Graphitschmiermechanismus weiterhin unvollständig. Zwei Modelle werden hierbei bis heute viel zitiert: das von Bragg postulierte, so genannte Deck-of-Card-Modell und das Adsorptionsmodell von Savage. Ersteres liefert keine eindeutige Erklärung zur Feuchtigkeitsabhängigkeit der Graphitschmierung und wurde experimentell widerlegt. Das Adsorptionsmodell von Savage bezieht die Wirkung der Wassermoleküle mit ein, wurde jedoch hauptsächlich auf atomar flachen Oberflächen oder für kleine Normalkräfte getestet. Die vorliegende Arbeit beschäftigt sich mit der Untersuchung des Schmierungsmechanismus von Graphit als Festschmierstoff und die tiefgreifende Erforschung der möglichen Einflussgrößen. In dieser Arbeit wurden deshalb Mikrotribometer-Gleitexperimente im Kugel-Platte-Kontakt durchgeführt, um die Graphitschmierung vor allem unter hohen Flächenpressungen zu untersuchen. Als Proben dienen hierfür mittels eines Airbrush-Sprühverfahren graphitbeschichteten Eisenplatten. Erste Parameterstudien widmeten sich dem Einfluss von Normalkraft und Schichtdicke und zeigten eine starke Korrelation sowie niedrigste Reibung bei höchster Normalkraft und dünnster Schichtdicke. Die Substrat-Beschichtungs-Adhäsion hat hierbei einen limitierenden Einfluss auf die Schichtlebensdauer, weshalb die Substratrauigkeit graduell variiert und untersucht wurde. Eine gute Reibminderung sowie lange Lebensdauer konnten auf die Bildung einer dünnen Kohlenstoffschicht zurückgeführt werden, welche bei industrie-nahen Oberflächenrauheiten gebildet wurde. Ein weiterer wichtiger Aspekt dieser Arbeit war im Anschluss die eingehende Analyse der Feuchtigkeitsabhängigkeit auf die Graphitschmierung. Mittels Transmissionselektronenmikroskopie konnte die Umformung von Graphit in turbostratischen Kohlenstoff nachgewiesen werden und somit ein neuer, erweiterter Schmiermechanismus vorgeschlagen werden. Diese in-situ-Bildung des turbostratischen Kohlenstoffs an der Gleitfläche wurde sowohl bei hohen als auch bei niedrigen Lasten beobachtet. Als letzter Aspekt wurde der Graphitschmierstoff unter Rollreibung getestet. Hierdurch konnte Korrelationen zur gewünschten Anwendung, einem Axialwälzlager, gezogen und wichtige Erkenntnisse gewonnen werden. Es wurde die Bildung eines dünnen Tribofilms auf dem Gegenkörper beobachtet und durch Raman-Spektroskopie bestätigt, welcher die tribologische Leistung der Graphitbeschichtung maßgeblich zu beeinflussen scheint