Numerical and experimental investigations on capillary-driven thin-film evaporation with applications in pumped two-phase loop and loop thermosyphon

Thin-film evaporation in solid-liquid-vapor interface has been the focal point of engineering research and industrial applications for decades. The objective of this dissertation is to systematically investigate the surface-tension (capillary)-driven thin-film evaporation in porous media and of a sessile droplet on a solid substrate using computational experimental methods. In Chapter 2, a mechanical-capillary-driven (hybrid) two-phase loop (HTPL) was used as a test platform to study the capillary-driven thin-film evaporation at a system level. Deionized water is the working fluid for the HTPL. A computational model for the HTPL using a thermal-hydraulic network was developed to predict the steady-state thermal performance and the evaporation mode transition in the HTPL. It was found that there are three distinctive evaporation modes (flooded, partially flooded, and capillary) which are determined by the pressure conditions in the liquid and vapor volumes of the evaporator. As the heat input increases, the evaporation mode is shifted from flooded to partially flooded to capillary mode. The capillary limit, the maximum heat flux limit of the thin-film evaporation, is raised by increasing the mechanical pump flow rate. In Chapter 3, a loop thermosyphon as a passive system was used to study the effects of the evaporator wick structure and properties on the capillary-driven thin-film evaporation. The effects of the evaporator wick base thickness and wick permeability on the evaporator thermal resistance and the capillary heat flux limit were numerically analyzed. A monolayer wick, which was made of mono-size sintered copper particles embedded in a single layer of a wire mesh, was used in the evaporator to lower the thermal resistance. The thermophysical and hydrodynamic properties (e.g. thermal resistance and permeability) of the monolayer wick for various liquid levels were calculated by computational fluid dynamics (CFD) simulations. A thermal-hydraulic network model of the loop thermosyphon was used to study the evaporation mode transition in the monolayer wick in the evaporator. The thermal-hydraulic network model was experimentally validated by the experimental results for three different evaporator designs employing multilayer and monolayer wick bases, and porous and tubular wick posts. The evaporation mode transition from flooded to thin-film evaporation was detected by the evaporator thermal resistance which is directly related with the liquid level in the monolayer wick base. In Chapter 4, an active flow control scheme was developed for the HTPL in an effort to control the capillary-driven thin-film evaporation in the evaporator. The relation between the capillary pressure head and the evaporation modes was established and used for the active flow control. An active flow algorithm was developed to control the mechanical pump flow rate to maintain the capillary pressure head in the evaporator constant, while operating under varying heat input. It was found that the active flow control greatly extends the operating range of the HTPL using the capillary thin-film evaporation and significantly reduces the pumping power consumption compared to a constant flow operation. The robustness of the active flow control was confirmed by operating the HTPL under a dynamic (on-off) heat input cycle along with the active control successfully to maintain the capillary pressure head at a preset value without temperature overshooting. In Chapter 5, the surface evaporation of a sessile droplet on solid substrates was numerically and experimentally investigated. A CFD model was developed to analyze the heat and mass transfer for the surface evaporation of a water droplet on solid substrates in ambient. The results from the CFD simulations were in good agreement with the experimental results for a water droplet evaporation on a hydrophobic-coated silicon substrate. It was found from the CFD simulations that the thermocapillary-driven flow (the Marangoni flow) and natural convection play a great role in the droplet evaporation and internal liquid circulation in the droplet. The effects of contact angle, thermal conductivity of the substrate, and ambient humidity on the droplet evaporation were numerically investigated and the results are discussed

An Optimized Dynamic Mode Decomposition Model Robust to Multiplicative Noise

Dynamic mode decomposition (DMD) is an efficient tool for decomposing spatio-temporal data into a set of low-dimensional modes, yielding the oscillation frequencies and the growth rates of physically significant modes. In this paper, we propose a novel DMD model that can be used for dynamical systems affected by multiplicative noise. We first derive a maximum a posteriori (MAP) estimator for the data-based model decomposition of a linear dynamical system corrupted by certain multiplicative noise. Applying penalty relaxation to the MAP estimator, we obtain the proposed DMD model whose epigraphical limits are the MAP estimator and the conventional optimized DMD model. We also propose an efficient alternating gradient descent method for solving the proposed DMD model, and analyze its convergence behavior. The proposed model is demonstrated on both the synthetic data and the numerically generated one-dimensional combustor data, and is shown to have superior reconstruction properties compared to state-of-the-art DMD models. Considering that multiplicative noise is ubiquitous in numerous dynamical systems, the proposed DMD model opens up new possibilities for accurate data-based modal decomposition.Comment: 35 pages, 10 figure

Few-Shot Keyword Spotting With Prototypical Networks

Recognizing a particular command or a keyword, keyword spotting has been widely used in many voice interfaces such as Amazon's Alexa and Google Home. In order to recognize a set of keywords, most of the recent deep learning based approaches use a neural network trained with a large number of samples to identify certain pre-defined keywords. This restricts the system from recognizing new, user-defined keywords. Therefore, we first formulate this problem as a few-shot keyword spotting and approach it using metric learning. To enable this research, we also synthesize and publish a Few-shot Google Speech Commands dataset. We then propose a solution to the few-shot keyword spotting problem using temporal and dilated convolutions on prototypical networks. Our comparative experimental results demonstrate keyword spotting of new keywords using just a small number of samples

The Effect Of Internal Capital Market Of Korean Large Business Groups On Investment Efficiency

This study examines whether the effect of funding through internal capital markets on investment efficiency is differentiated by the incentives of controlling shareholders as measured by the divergence between cash flow rights and voting rights of controlling shareholders (hereafter, wedge). To empirically analyze hypotheses of this study, 1,189 firm-year observations were collected from Korean firms listed on the Korea Composite Stock Price Index (KOSPI) belonging to a large business group designated by the Korea Fair Trade Commission over the period from 2005 to 2012. The results of the analysis are as follows. First, we find that the magnitude of internal funding, as measured by total payables to the related parties, is positively (+) associated with investment inefficiency. Second, the interaction variables of total payables to the related parties and the wedge have a significant positive (+) effect on investment inefficiency. In other words, the deterioration of investment efficiency due to the increase in total payables to the related parties was mainly caused by firms with a big wedge. This result suggests that the effect of internal capital markets on investment efficiency of large business groups may be differentiated by the wedge that is proxy of the controlling shareholder’s incentive. This study provides additional evidence on previous studies on the investment efficiency of large business groups by considering both the internal capital market and incentives for funding using the internal capital market, which are important factors affecting the investment of large corporate groups. Also, the results of this study are expected to provide implications for the regulatory policy of large business groups which have recently become an issue in Korea

Reverse Block Mall - Collectivization as Strategy Against Spatial Monopolization in Toronto

Amidst an unprecedented pace of high-rise developments along Toronto’s main streets, the issue of homogenization of the urban environment has been approached mainly from the perspective of architectural design. Accordingly, various efforts to preserve and reinvigorate the streetscape have focused on aesthetical features such as attention to human-scale details, retention of historic facades, and variating of building massing to recreate a sense of diversity. Despite this effort, the ubiquity of run-of-the-mill glass towers and generic chain stores that inevitably occupy the ‘renewed’ streetscape attests to the ineffectiveness of this approach. This thesis argues that the reliance on design-based solutions as a fix for homogenization is ineffective because it overlooks the underlying monopolization of ownership that occurs as part of the development process. The displacement of existing tenant and owner bodies, and the consolidation of properties homogenizes the range of self-expression and spatial platforms that provides the basis for design authenticity. Therefore, any effort to preserve and reinvigorate the streetscape must begin with an alternative strategy of development that is grounded on the preservation of existing range of buildings, lots, and establishments, and enhancement of economic viability of small-scale ownership as its pre-condition. The proposed intervention begins by identifying restrictions embodied in urban form, design policy, and development process that degrade the economic and spatial performance of small-scale properties. To mitigate their impact, the collectivization of existing properties on a block of historic Yonge Street is proposed as a central strategy with several corollary outcomes: air-right development, activation of laneway space, and facilitation of internal spatial transactions. The sale of collective air-right enables a parallel process of densification to occur while creating synergies with the existing base-level properties. The earnings from the sale provide the basis for the activation of the rear- laneway and the commercial utilization of the building rear-faces, providing an extension of the public domain and increased autonomy for the tenants and owners. Finally, facilitation of self-guided spatial transactions between the tenants establishes iterative optimization and diversification of space which improves commercial performance and the range of self-expression. The culminating effect of these processes attempts to define a new development typology that not only precludes displacement, but forms an urban ‘place’ that is architecturally distinct, culturally rich, and economically viable

Spatial Analytics with Hospitality Big Data: Examining the Impact of Locational Determinants on Customer Satisfaction in the U.S. Hotel Market

Although hotel location has been recognized as one of the important factors affecting hotel selection and guest satisfaction, relatively few studies have examined guest satisfaction with hotel location and its locational determinants at a macro level. This study aims to identify the locational determinants of hotel guest satisfaction through big data spatial analytics via a case study of 5,302 hotels in 151 cities in the U.S. Based on the framework of hotel location satisfaction, we classified all location-related factors into three categories: accessibility to points of interest, transport convenience, and surrounding environment. Our findings indicated that hotel property’s proximity to city area, landmark, park, shopping center, and highway as well as, attraction-driven tourism industry specialization, and hotel industry agglomeration were significant determinants. Furthermore, the impacts of these factors were spatially heterogeneous. These findings can provide geographical insights that are critical for developing a customer service experience and satisfaction model

A numerically efficient output-only system-identification framework for stochastically forced self-sustained oscillators

Self-sustained oscillations are ubiquitous in nature and engineering. In this paper, we propose a novel output-only system-identification framework for identifying the system parameters of a self-sustained oscillator affected by Gaussian white noise. A Langevin model that characterizes the self-sustained oscillator is postulated, and the corresponding Fokker--Planck equation is derived from stochastic averaging. From the drift and diffusion terms of the Fokker--Planck equation, unknown parameters of the system are identified. We develop a numerically efficient algorithm for enhancing the accuracy of parameter identification. In particular, a modified Levenberg--Marquardt optimization algorithm tailored to output-only system identification is introduced. The proposed framework is demonstrated on both numerical and experimental oscillators with varying system parameters that develop into self-sustained oscillations. The results show that the computational cost required for performing the system identification is dramatically reduced by using the proposed framework. Also, system parameters that were difficult to be extracted with the existing method could be efficiently computed with the system identification method developed in this study. Pertaining to the robustness and computational efficiency of the presented framework, this study can contribute to an accurate and fast diagnosis of dynamical systems under stochastic forcing.Comment: 17 pages, 10 figure