ITC/USA 2015 Conference Proceedings / The Fifty-First Annual International Telemetering Conference and Technical Exhibition / October 26-29, 2015 / Bally's Hotel & Convention Center, Las Vegas, NV / This paper describes a method in which users realize the benefits of a standards-based method for capturing and evaluating verification and validation (V&V) rules within and across metadata instance documents. The method uses a natural language based syntax for the T&E metadata V&V rule set in order to abstract the highly technical rule languages to a domain-specific syntax. As a result, the domain expert can easily specify, validate and manage the specification and validation of the rules themselves. Our approach is very flexible in that under the hood, the method automatically translates rules to a host of target rule languages. We validated our method in a multi-vendor scenario involving Metadata Description Language (MDL) and Instrumentation Hardware Abstraction Language (IHAL) instance documents, user constraints, and domain constraints. The rules are captured in natural language, and used to perform V&V within a single metadata instance document and across multiple metadata instance documents.

付記する学位プログラム名: デザイン学大学院連携プログラム / 京都大学 / 0048 / 新制・課程博士 / 博士(工学) / 甲第22772号 / 工博第4771号 / 新制||工||1746(附属図書館) / 京都大学大学院工学研究科機械理工学専攻 / (主査)教授 椹木 哲夫, 教授 松原 厚, 教授 小森 雅晴 / 学位規則第4条第1項該当 / Doctor of Philosophy (Engineering) / Kyoto University / DFAM

<div>The current study is aimed at developing a well-posed and objective, i.e., frame invariant, Eulerian one-dimensional (1D) Two-Fluid Model (TFM) to predict flow regime transition from dispersed to clustered bubbly and slug flow for vertical adiabatic two-phase flows. Two-phase flows in general are characterized by local material wave or void fraction wave instabilities and flow regime transitions are one of the important consequences of these instabilities. The physical mechanism of wake entrainment for clustering of dispersed bubbles is proposed, leading to formation of bubble clusters and Taylor bubbles. The focus of the work is on simulation of the local interfacial structures for bubble clusters and Taylor bubbles, using a well-posed, unstable and non-linearly bounded 1D Shallow Water TFM.</div><div><br></div><div>The first part of the current study investigates the dynamic behavior of the well posed 1D mechanistic TFM obtained from the averaging approach of Ishii [1], due to wake entrainment instability. For this, a 1D Shallow Water TFM derived from the 1D mechanistic TFM is used, which retains the same dynamic behavior as that of the latter at short wavelengths and the required wake entrainment force is derived mechanistically. Three stability approaches are followed to study the dynamic behavior of the 1D Shallow Water TFM: characteristics, dispersion analysis, and nonlinear numerical simulations. An in-house code is used for the 1D numerical simulations of the growth of void fraction waves due to wake entrainment. The simulation results are validated with the experimental data of Cheng and Azzopardi [2] and Song et al. [3] To conclude the first part, the 1D results of the two-equation Shallow Water TFM are carried over to the complete four-equation TFM for quasi 1D simulations using the commercial CFD code of ANSYS Fluent.</div><div><br></div>As an alternative to the mechanistic approach, which is based on Newtonian mathematics, a variational approach based on Lagrangian and Hamiltonian mathematics is used in the second part of the thesis. While the mechanistic approach operates in terms of forces acting on the two-phase mixture, the variational approach operates in terms of energies of the two-phase system. To derive the equations of motion using the variational approach, the extended Hamilton principle of least action is applied to the Lagrangian density of the two-phase mixture. One of the appealing features<br>17<br>of this procedure is that the derived equations of motion are objective (Geurst [4]), in particular the added mass terms.<br>Thus, the second part of the current study focuses on deriving an objective, well-posed and unstable 1D TFM as well as developing a constitutive model for the wake entrainment effect using the variational method. Additional momentum transfer terms present in both the liquid phase and gas phase momentum equations, which render the variational TFM objective, are discussed. The variational method is then used to derive the 1D Shallow Water TFM using the fixed flux assumption. The conservative interfacial momentum transfer terms require formulation of the inertial coupling between the phases. Potential flow theory is first used to derive the inertial coupling coefficient for a single bubble and then for a pair of bubbles to consider interaction between the two bubbles. Then, a lumped parameter model is used to derive the inertial coupling coefficient for the wake entrainment effect. A local drag coefficient is obtained for the non-conservative interfacial drag force from the experimental data using kinematic approximation, i.e., force balance between drag and gravity. The linear and non-linear stability analyses are used to address the stability of the 1D variational Shallow Water TFM. The presence of appropriate short-wave physics makes the 1D Shallow Water TFM hyperbolic well-posed and kinematically unstable. Finally, numerical simulations are performed to demonstrate the development of void fraction waves due wake entrainment. The growth of void fraction waves is non-linearly bounded, i.e., Lyapunov stable. The simulation results are compared with the experimental data to validate the propagation properties of void fraction waves for bubble clusters and Taylor bubbles. This work illustrates the short-wave two-phase flow simulation capability of the TFM for the bubbly to slug flow regime transition.

<div>Adsorbent technology is widely used in many industrial applications including waste heat recovery, water purification, and atmospheric revitalization in confined habitations. Astronauts depend on adsorbent-based systems to remove metabolic carbon dioxide (CO₂) from the cabin atmosphere; as NASA prepares for the journey to Mars, engineers are redesigning the adsorbent-based system for reduced weight and optimal efficiency. These efforts hinge upon the development of accurate, predictive models, as simulations are increasingly relied upon to save cost and time over the traditional design-build-test approach. Engineers rely on simplified models to reduce computational cost and enable parametric optimizations. Amongst these simplified models is the axially dispersed plug-flow model for predicting the adsorbate concentration during flow through an adsorbent bed. This model is ubiquitously used in designing fixed-bed adsorption systems. The current work aims to improve the accuracy of the axially dispersed plug-flow model because of its wide-spread use. This dissertation identifies the critical model inputs that drive the overall uncertainty in important output quantities then systematically improves the measurement and prediction of these input parameters. Limitations of the axially dispersed plug-flow model are also discussed, and recommendations made for identifying failure of the plug-flow assumption.</div><div><br></div><div>An uncertainty and sensitivity analysis of an axially disperse plug-flow model is first presented. Upper and lower uncertainty bounds for each of the model inputs are found by comparing empirical correlations against experimental data from the literature. Model uncertainty is then investigated by independently varying each model input between its individual upper and lower uncertainty bounds then observing the relative change in predicted effluent concentration and temperature (<i>e.g.</i>, breakthrough time, bed capacity, and effluent temperature). This analysis showed that the LDF mass transfer coefficient is the largest source of uncertainty. Furthermore, the uncertainty analysis reveals that ignoring the effect of wall-channeling on apparent axial dispersion can cause significant error in the predicted breakthrough times of small-diameter beds.</div><div><br></div><div>In addition to LDF mass transfer coefficient and axial-dispersion, equilibrium isotherms are known to be strong lever arms and a potentially dominant source of model error. As such, detailed analysis of the equilibrium adsorption isotherms for zeolite 13X was conducted to improve the fidelity of CO₂ and H₂O on equilibrium isotherms compared to extant data. These two adsorbent/adsorbate pairs are of great interest as NASA plans to use zeolite 13X in the next generation atmospheric revitalization system. Equilibrium isotherms describe a sorbent’s maximum capacity at a given temperature and adsorbate (<i>e.g.</i>, CO₂ or H₂O) partial pressure. New isotherm data from NASA Ames Research Center and NASA Marshall Space Flight Center for CO₂ and H₂O adsorption on zeolite 13X are presented. These measurements were carefully collected to eliminate sources of bias in previous data from the literature, where incomplete activation resulted in a reduced capacity. Several models are fit to the new equilibrium isotherm data and recommendations of the best model fit are made. The best-fit isotherm models from this analysis are used in all subsequent modeling efforts discussed in this dissertation.</div><div><br></div><div>The last two chapters examine the limitations of the axially disperse plug-flow model for predicting breakthrough in confined geometries. When a bed of pellets is confined in a rigid container, packing heterogeneities near the wall lead to faster flow around the periphery of the bed (<i>i.e.</i>, wall channeling). Wall-channeling effects have long been considered negligible for beds which hold more than 20 pellets across; however, the present work shows that neglecting wall-channeling effects on dispersion can yield significant errors in model predictions. There is a fundamental gap in understanding the mechanisms which control wall-channeling driven dispersion. Furthermore, there is currently no way to predict wall channeling effects a priori or even to identify what systems will be impacted by it. This dissertation aims to fill this gap using both experimental measurements and simulations to identify mechanisms which cause the plug-flow assumption to fail.</div><div><br></div><div>First, experimental evidence of wall-channeling in beds, even at large bed-to-pellet diameter ratios (<i>d</i>_bed/<i>d</i>_p=48) is presented. These experiments are then used to validate a method for accurately extracting mass transfer coefficients from data affected by significant wall channeling. The relative magnitudes of wall-channeling effects are shown to be a function of the adsorption/adsorbate pair and geometric confinement (<i>i.e.</i>, bed size). Ultimately, the axially disperse plug-flow model fails to capture the physics of breakthrough when nonplug-flow conditions prevail in the bed.</div><div><br></div><div>The final chapter of this dissertation develops a two-dimensional (2-D) adsorption model to examine the interplay of wall-channeling and adsorption kinetics and the adsorbent equilibrium capacity on breakthrough in confined geometries. The 2-D model incorporates the effect of radial variations in porosity on the velocity profile and is shown to accurately capture the effect of wall-channeling on adsorption behavior. The 2-D model is validated against experimental data, and then used to investigate whether capacity or adsorption kinetics cause certain adsorbates to exhibit more significant radial variations in concentration compared than others. This work explains channeling effects can vary for different adsorbate and/or adsorbent pairs—even under otherwise identical conditions—and highlights the importance of considering adsorption kinetics in addition to the traditional <i>d</i>_bed/<i>d</i>_p criteria.</div><div><br></div><div>This dissertation investigates key gaps in our understanding of fixed-bed adsorption. It will deliver insight into how these missing pieces impact the accuracy of predictive models and provide a means for reconciling these errors. The culmination of this work will be an accurate, predictive model that assists in the simulation-based design of the next-generation atmospheric revitalization system for humans’ journey to Mars.</div>