Effect of segmented anodes on the performance and plume of a hall thruster

Development of alternative propellants for Hall thruster operation is an active area of research. Xenon is the current propellant of choice for Hall thrusters, but can be costly in large thrusters and for extended test periods. Condensible propellants may offer an alternative to xenon, as they will not require costly active pumping to remove from a test facility, and may be less expensive to purchase. A method has been developed which uses segmented electrodes in the discharge channel of a Hall thruster to divert discharge current to and from the main anode and thus control the anode temperature. By placing a propellant reservoir in the anode, the evaporation rate, and hence, mass flow of propellant can be controlled. Segmented electrodes for thermal control of a Hall thruster represent a unique strategy of thruster design, and thus the performance of the thruster must be measured to determine the effect the electrodes have on the thruster. Furthermore, the source of any changes in thruster performance due to the adjustment of discharge current between the shims and the main anode must be characterized. A Hall thruster was designed and constructed with segmented electrodes. It was then tested at anode voltages between 300 and 400 V and mass flows between 4 and 6 mg/s, as well as 100%, 75%, 50%, 25%, and <5% of the discharge current on the shim electrodes. The level of current on the shims was adjusted by changing the shim voltage. At each operating point, the thruster performance, plume divergence, ion energy, and multiply charged ion fraction were measured performance exhibited a small change with the level of discharge current on the shim electrodes. Thrust and specific impulse increased by as much as 6% and 7.7%, respectively, as discharge current was shifted from the main anode to the shims at constant anode voltage. Thruster efficiency did not change. Plume divergence was reduced by approximately 4 degrees of half-angle at high levels of current on the shims and at all combinations of mass flow and anode voltage. The fraction of singly charged xenon in the thruster plume varied between approximately 80% and 95% as the anode voltage and mass flow were changed, but did not show a significant change with shim current. Doubly and triply charged xenon made up the remainder of the ions detected. Ion energy exhibited a mixed behavior. The highest voltage present in the thruster largely dictated the most probable energy; either shim or anode voltage, depending on which was higher. The overall change in most probable ion energy was 20-30 eV, the majority of which took place while the shim voltage was higher than the anode voltage. The thrust, specific impulse, plume divergence, and ion energy all indicate that the thruster is capable of a higher performance output at high levels of discharge current on the shims. The lack of a change in efficiency and fraction of multiply charged ions indicate that the thruster can be operated at any level of current on the shims without detrimental effect, and thus a condensible propellant thruster can control the anode temperature without a decrease in efficiency or a change in the multiply charged ion fraction.

Adaptive control of sinusoidal brushless DC motor actuators

Electrical Power Assisted Steering system (EPAS) will likely be used on future automotive power steering systems. The sinusoidal brushless DC (BLDC) motor has been identified as one of the most suitable actuators for the EPAS application. Motor characteristic variations, which can be indicated by variations of the motor parameters such as the coil resistance and the torque constant, directly impart inaccuracies in the control scheme based on the nominal values of parameters and thus the whole system performance suffers. The motor controller must address the time-varying motor characteristics problem and maintain the performance in its long service life. In this dissertation, four adaptive control algorithms for brushless DC (BLDC) motors are explored. The first algorithm engages a simplified inverse dq-coordinate dynamics controller and solves for the parameter errors with the q-axis current (iq) feedback from several past sampling steps. The controller parameter values are updated by slow integration of the parameter errors. Improvement such as dynamic approximation, speed approximation and Gram-Schmidt orthonormalization are discussed for better estimation performance. The second algorithm is proposed to use both the d-axis current (id) and the q-axis current (iq) feedback for parameter estimation since id always accompanies iq. Stochastic conditions for unbiased estimation are shown through Monte Carlo simulations. Study of the first two adaptive algorithms indicates that the parameter estimation performance can be achieved by using more history data. The Extended Kalman Filter (EKF), a representative recursive estimation algorithm, is then investigated for the BLDC motor application. Simulation results validated the superior estimation performance with the EKF. However, the computation complexity and stability may be barriers for practical implementation of the EKF. The fourth algorithm is a model reference adaptive control (MRAC) that utilizes the desired motor characteristics as a reference model. Its stability is guaranteed by Lyapunov’s direct method. Simulation shows superior performance in terms of the convergence speed and current tracking. These algorithms are compared in closed loop simulation with an EPAS model and a motor speed control application. The MRAC is identified as the most promising candidate controller because of its combination of superior performance and low computational complexity. A BLDC motor controller developed with the dq-coordinate model cannot be implemented without several supplemental functions such as the coordinate transformation and a DC-to-AC current encoding scheme. A quasi-physical BLDC motor model is developed to study the practical implementation issues of the dq-coordinate control strategy, such as the initialization and rotor angle transducer resolution. This model can also be beneficial during first stage development in automotive BLDC motor applications.

Integrated solar energy and absorption cooling model for HVAC (heating, ventilating, and air conditioning) applications in buildings

The demands in production and associate costs at power generation through non renewable resources are increasing at an alarming rate. Solar energy is one of the renewable resource that has the potential to minimize this increase. Utilization of solar energy have been concentrated mainly on heating application. The use of solar energy in cooling systems in building would benefit greatly achieving the goal of non-renewable energy minimization. The approaches of solar energy heating system research done by initiation such as University of Wisconsin at Madison and building heat flow model research conducted by Oklahoma State University can be used to develop and optimize solar cooling building system. The research uses two approaches to develop a Graphical User Interface (GUI) software for an integrated solar absorption cooling building model, which is capable of simulating and optimizing the absorption cooling system using solar energy as the main energy source to drive the cycle. The software was then put through a number of litmus test to verify its integrity. The litmus test was conducted on various building cooling system data sets of similar applications around the world. The output obtained from the software developed were identical with established experimental results from the data sets used. Software developed by other research are catered for advanced users. The software developed by this research is not only reliable in its code integrity but also through its integrated approach which is catered for new entry users. Hence, this dissertation aims to correctly model a complete building with the absorption cooling system in appropriate climate as a cost effective alternative to conventional vapor compression system.

Mechanical modeling of Intraneural Ganglion Cyst

Intraneural Ganglion Cyst is a 200 year old mystery related to nerve injury which is yet to be solved. Current treatments for the above problem are relatively simple procedures related to removal of cystic contents from the nerve. However, these treatments may result into neuropathic pain and recurrence of the cyst. The articular theory proposed by Spinner et al., (Spinner et al. 2003) takes into consideration the neurological deficit in Common Peroneal Nerve (CPN) branch of the sciatic nerve and affirms that in addition to the above treatments, ligation of articular branch results into foolproof eradication of the deficit. Mechanical Modeling of the Affected Nerve Cross Section will reinforce the articular theory (Spinner et al. 2003). As the cyst propagates, it compresses the neighboring fascicles and the nerve cross section appears like a signet ring. Hence, in order to mechanically model the affected nerve cross section; computational methods capable of modeling excessively large deformations are required. Traditional FEM produces distorted elements while modeling such deformations, resulting into inaccuracies and premature termination of the analysis. The methods described in this Master’s Thesis are effective enough to be able to simulate such deformations. The results obtained from the model adequately resemble the MRI image obtained at the same location and shows an appearance of a signet ring. This Master’s Thesis describes the neurological deficit in brief followed by detail explanation of the advanced computational methods used to simulate this problem. Finally, qualitative results show the resemblance of mechanical model to MRI images of the Nerve Cross Section at the same location validating the capability of these methods to study this neurological deficit.

Static and dynamic contact angle measurement on rough surfaces using sessile drop profile analysis with application to water management in low temperature fuel cells

Fuel Cells are a promising alternative energy technology. One of the biggest problems that exists in fuel cell is that of water management. A better understanding of wettability characteristics in the fuel cells is needed to alleviate the problem of water management. Contact angle data on gas diffusion layers (GDL) of the fuel cells can be used to characterize the wettability of GDL in fuel cells. A contact angle measurement program has been developed to measure the contact angle of sessile drops from drop images. Digitization of drop images induces pixel errors in the contact angle measurement process. The resulting uncertainty in contact angle measurement has been analyzed. An experimental apparatus has been developed for contact angle measurements at different temperature, with the feature to measure advancing and receding contact angles on gas diffusion layers of fuel cells.

Comprehensive review and application of particle image velocimetry

For a fluid dynamics experimental flow measurement technique, particle image velocimetry (PIV) provides significant advantages over other measurement techniques in its field. In contrast to temperature and pressure based probe measurements or other laser diagnostic techniques including laser Doppler velocimetry (LDV) and phase Doppler particle analysis (PDPA), PIV is unique due to its whole field measurement capability, non-intrusive nature, and ability to collect a vast amount of experimental data in a short time frame providing both quantitative and qualitative insight. These properties make PIV a desirable measurement technique for studies encompassing a broad range of fluid dynamics applications. However, as an optical measurement technique, PIV also requires a substantial technical understanding and application experience to acquire consistent, reliable results. Both a technical understanding of particle image velocimetry and practical application experience are gained by applying a planar PIV system at Michigan Technological University’s Combustion Science Exploration Laboratory (CSEL) and Alternative Fuels Combustion Laboratory (AFCL). Here a PIV system was applied to non-reacting and reacting gaseous environments to make two component planar PIV as well as three component stereographic PIV flow field velocity measurements in conjunction with chemiluminescence imaging in the case of reacting flows. This thesis outlines near surface flow field characteristics in a tumble strip lined channel, three component velocity profiles of non-reacting and reacting swirled flow in a swirl stabilized lean condition premixed/prevaporized-fuel model gas turbine combustor operating on methane at 5-7 kW, and two component planar PIV measurements characterizing the AFCL’s 1.1 liter closed combustion chamber under dual fan driven turbulent mixing flow.

Dynamic modeling of active regeneration in catalyzed and non-catalyzed diesel particulate filters

Particulate matter (PM) emissions standards set by the US Environmental Protection Agency (EPA) have become increasingly stringent over the years. The EPA regulation for PM in heavy duty diesel engines has been reduced to 0.01 g/bhp-hr for the year 2010. Heavy duty diesel engines make use of an aftertreatment filtration device, the Diesel Particulate Filter (DPF). DPFs are highly efficient in filtering PM (known as soot) and are an integral part of 2010 heavy duty diesel aftertreatment system. PM is accumulated in the DPF as the exhaust gas flows through it. This PM needs to be removed by oxidation periodically for the efficient functioning of the filter. This oxidation process is also known as regeneration. There are 2 types of regeneration processes, namely active regeneration (oxidation of PM by external means) and passive oxidation (oxidation of PM by internal means). Active regeneration occurs typically in high temperature regions, about 500 - 600 °C, which is much higher than normal diesel exhaust temperatures. Thus, the exhaust temperature has to be raised with the help of external devices like a Diesel Oxidation Catalyst (DOC) or a fuel burner. The O2 oxidizes PM producing CO2 as oxidation product. In passive oxidation, one way of regeneration is by the use of NO2. NO2 oxidizes the PM producing NO and CO2 as oxidation products. The passive oxidation process occurs at lower temperatures (200 - 400 °C) in comparison to the active regeneration temperatures. Generally, DPF substrate walls are washcoated with catalyst material to speed up the rate of PM oxidation. The catalyst washcoat is observed to increase the rate of PM oxidation. The goal of this research is to develop a simple mathematical model to simulate the PM depletion during the active regeneration process in a DPF (catalyzed and non-catalyzed). A simple, zero-dimensional kinetic model was developed in MATLAB. Experimental data required for calibration was obtained by active regeneration experiments performed on PM loaded mini DPFs in an automated flow reactor. The DPFs were loaded with PM from the exhaust of a commercial heavy duty diesel engine. The model was calibrated to the data obtained from active regeneration experiments. Numerical gradient based optimization techniques were used to estimate the kinetic parameters of the model.

Development of an optimization model for biofuel facility size and location and a simulation model for design of a biofuel supply chain

To mitigate greenhouse gas (GHG) emissions and reduce U.S. dependence on imported oil, the United States (U.S.) is pursuing several options to create biofuels from renewable woody biomass (hereafter referred to as “biomass”). Because of the distributed nature of biomass feedstock, the cost and complexity of biomass recovery operations has significant challenges that hinder increased biomass utilization for energy production. To facilitate the exploration of a wide variety of conditions that promise profitable biomass utilization and tapping unused forest residues, it is proposed to develop biofuel supply chain models based on optimization and simulation approaches. The biofuel supply chain is structured around four components: biofuel facility locations and sizes, biomass harvesting/forwarding, transportation, and storage. A Geographic Information System (GIS) based approach is proposed as a first step for selecting potential facility locations for biofuel production from forest biomass based on a set of evaluation criteria, such as accessibility to biomass, railway/road transportation network, water body and workforce. The development of optimization and simulation models is also proposed. The results of the models will be used to determine (1) the number, location, and size of the biofuel facilities, and (2) the amounts of biomass to be transported between the harvesting areas and the biofuel facilities over a 20-year timeframe. The multi-criteria objective is to minimize the weighted sum of the delivered feedstock cost, energy consumption, and GHG emissions simultaneously. Finally, a series of sensitivity analyses will be conducted to identify the sensitivity of the decisions, such as the optimal site selected for the biofuel facility, to changes in influential parameters, such as biomass availability and transportation fuel price. Intellectual Merit The proposed research will facilitate the exploration of a wide variety of conditions that promise profitable biomass utilization in the renewable biofuel industry. The GIS-based facility location analysis considers a series of factors which have not been considered simultaneously in previous research. Location analysis is critical to the financial success of producing biofuel. The modeling of woody biomass supply chains using both optimization and simulation, combing with the GIS-based approach as a precursor, have not been done to date. The optimization and simulation models can help to ensure the economic and environmental viability and sustainability of the entire biofuel supply chain at both the strategic design level and the operational planning level. Broader Impacts The proposed models for biorefineries can be applied to other types of manufacturing or processing operations using biomass. This is because the biomass feedstock supply chain is similar, if not the same, for biorefineries, biomass fired or co-fired power plants, or torrefaction/pelletization operations. Additionally, the research results of this research will continue to be disseminated internationally through publications in journals, such as Biomass and Bioenergy, and Renewable Energy, and presentations at conferences, such as the 2011 Industrial Engineering Research Conference. For example, part of the research work related to biofuel facility identification has been published: Zhang, Johnson and Sutherland [2011] (see Appendix A). There will also be opportunities for the Michigan Tech campus community to learn about the research through the Sustainable Future Institute.

Modeling mechanical response of heterogeneous materials

Heterogeneous materials are ubiquitous in nature and as synthetic materials. These materials provide unique combination of desirable mechanical properties emerging from its heterogeneities at different length scales. Future structural and technological applications will require the development of advanced light weight materials with superior strength and toughness. Cost effective design of the advanced high performance synthetic materials by tailoring their microstructure is the challenge facing the materials design community. Prior knowledge of structure-property relationships for these materials is imperative for optimal design. Thus, understanding such relationships for heterogeneous materials is of primary interest. Furthermore, computational burden is becoming critical concern in several areas of heterogeneous materials design. Therefore, computationally efficient and accurate predictive tools are highly essential. In the present study, we mainly focus on mechanical behavior of soft cellular materials and tough biological material such as mussel byssus thread. Cellular materials exhibit microstructural heterogeneity by interconnected network of same material phase. However, mussel byssus thread comprises of two distinct material phases. A robust numerical framework is developed to investigate the micromechanisms behind the macroscopic response of both of these materials. Using this framework, effect of microstuctural parameters has been addressed on the stress state of cellular specimens during split Hopkinson pressure bar test. A voronoi tessellation based algorithm has been developed to simulate the cellular microstructure. Micromechanisms (microinertia, microbuckling and microbending) governing macroscopic behavior of cellular solids are investigated thoroughly with respect to various microstructural and loading parameters. To understand the origin of high toughness of mussel byssus thread, a Genetic Algorithm (GA) based optimization framework has been developed. It is found that two different material phases (collagens) of mussel byssus thread are optimally distributed along the thread. These applications demonstrate that the presence of heterogeneity in the system demands high computational resources for simulation and modeling. Thus, Higher Dimensional Model Representation (HDMR) based surrogate modeling concept has been proposed to reduce computational complexity. The applicability of such methodology has been demonstrated in failure envelope construction and in multiscale finite element techniques. It is observed that surrogate based model can capture the behavior of complex material systems with sufficient accuracy. The computational algorithms presented in this thesis will further pave the way for accurate prediction of macroscopic deformation behavior of various class of advanced materials from their measurable microstructural features at a reasonable computational cost.

Control design and genetic algorithm optimization for electrostatic MEMS

This dissertation discusses structural-electrostatic modeling techniques, genetic algorithm based optimization and control design for electrostatic micro devices. First, an alternative modeling technique, the interpolated force model, for electrostatic micro devices is discussed. The method provides improved computational efficiency relative to a benchmark model, as well as improved accuracy for irregular electrode configurations relative to a common approximate model, the parallel plate approximation model. For the configuration most similar to two parallel plates, expected to be the best case scenario for the approximate model, both the parallel plate approximation model and the interpolated force model maintained less than 2.2% error in static deflection compared to the benchmark model. For the configuration expected to be the worst case scenario for the parallel plate approximation model, the interpolated force model maintained less than 2.9% error in static deflection while the parallel plate approximation model is incapable of handling the configuration. Second, genetic algorithm based optimization is shown to improve the design of an electrostatic micro sensor. The design space is enlarged from published design spaces to include the configuration of both sensing and actuation electrodes, material distribution, actuation voltage and other geometric dimensions. For a small population, the design was improved by approximately a factor of 6 over 15 generations to a fitness value of 3.2 fF. For a larger population seeded with the best configurations of the previous optimization, the design was improved by another 7% in 5 generations to a fitness value of 3.0 fF. Third, a learning control algorithm is presented that reduces the closing time of a radiofrequency microelectromechanical systems switch by minimizing bounce while maintaining robustness to fabrication variability. Electrostatic actuation of the plate causes pull-in with high impact velocities, which are difficult to control due to parameter variations from part to part. A single degree-of-freedom model was utilized to design a learning control algorithm that shapes the actuation voltage based on the open/closed state of the switch. Experiments on 3 test switches show that after 5-10 iterations, the learning algorithm lands the switch with an impact velocity not exceeding 0.2 m/s, eliminating bounce.

Effect of high order interpolation in the stability and efficiency of the time-integration process in vorticity-velocity CFD algorithms

The numerical solution of the incompressible Navier-Stokes Equations offers an effective alternative to the experimental analysis of Fluid-Structure interaction i.e. dynamical coupling between a fluid and a solid which otherwise is very complex, time consuming and very expensive. To have a method which can accurately model these types of mechanical systems by numerical solutions becomes a great option, since these advantages are even more obvious when considering huge structures like bridges, high rise buildings, or even wind turbine blades with diameters as large as 200 meters. The modeling of such processes, however, involves complex multiphysics problems along with complex geometries. This thesis focuses on a novel vorticity-velocity formulation called the KLE to solve the incompressible Navier-stokes equations for such FSI problems. This scheme allows for the implementation of robust adaptive ODE time integration schemes and thus allows us to tackle the various multiphysics problems as separate modules. The current algorithm for KLE employs a structured or unstructured mesh for spatial discretization and it allows the use of a self-adaptive or fixed time step ODE solver while dealing with unsteady problems. This research deals with the analysis of the effects of the Courant-Friedrichs-Lewy (CFL) condition for KLE when applied to unsteady Stoke’s problem. The objective is to conduct a numerical analysis for stability and, hence, for convergence. Our results confirmthat the time step ∆t is constrained by the CFL-like condition ∆t ≤ const. hα, where h denotes the variable that represents spatial discretization.

Nanomechanics of cellulose crystals and cellulose-based polymer composites

Cellulose-polymer composites have potential applications in aerospace and transportation areas where lightweight materials with high mechanical properties are needed. In addition, these economical and biodegradable composites have been shown to be useful as polymer electrolytes, packaging structures, optoelectronic devices, and medical implants such as wound dressing and bone scaffolds. In spite of the above mentioned advantages and potential applications, due to the difficulties associated with synthesis and processing techniques, application of cellulose crystals (micro and nano sized) for preparation of new composite systems is limited. Cellulose is hydrophilic and polar as opposed to most of common thermoplastics, which are non-polar. This results in complications in addition of cellulose crystals to polymer matrices, and as a result in achieving sufficient dispersion levels, which directly affects the mechanical properties of the composites. As in other composite materials, the properties of cellulose-polymer composites depend on the volume fraction and the properties of individual phases (the reinforcement and the polymer matrix), the dispersion quality of the reinforcement through the matrix and the interaction between CNCs themselves and CNC and the matrix (interphase). In order to develop economical cellulose-polymer composites with superior qualities, the properties of individual cellulose crystals, as well as the effect of dispersion of reinforcements and the interphase on the properties of the final composites should be understood. In this research, the mechanical properties of CNC polymer composites were characterized at the macro and nano scales. A direct correlation was made between: Dispersion quality and macro-mechanical properties Nanomechanical properties at the surface and tensile properties CNC diameter and interphase thickness Lastly, individual CNCs from different sources were characterized and for the first time size-scale effect on their nanomechanical properties were reported. Then the effect of CNC surface modification on the mechanical properties was studied and correlated to the crystalline structure of these materials.

Laser Thomson scattering measurements of electron temperature and density in a Hall-effect plasma

Hall-effect thrusters (HETs) are compact electric propulsion devices with high specific impulse used for a variety of space propulsion applications. HET technology is well developed but the electron properties in the discharge are not completely understood, mainly due to the difficulty involved in performing accurate measurements in the discharge. Measurements of electron temperature and density have been performed using electrostatic probes, but presence of the probes can significantly disrupt thruster operation, and thus alter the electron temperature and density. While fast-probe studies have expanded understanding of HET discharges, a non-invasive method of measuring the electron temperature and density in the plasma is highly desirable. An alternative to electrostatic probes is a non-perturbing laser diagnostic technique that measures Thomson scattering from the plasma. Thomson scattering is the process by which photons are elastically scattered from the free electrons in a plasma. Since the electrons have thermal energy their motion causes a Doppler shift in the scattered photons that is proportional to their velocity. Like electrostatic probes, laser Thomson scattering (LTS) can be used to determine the temperature and density of free electrons in the plasma. Since Thomson scattering measures the electron velocity distribution function directly no assumptions of the plasma conditions are required, allowing accurate measurements in anisotropic and non-Maxwellian plasmas. LTS requires a complicated measurement apparatus, but has the potential to provide accurate, non-perturbing measurements of electron temperature and density in HET discharges. In order to assess the feasibility of LTS diagnostics on HETs non-invasive measurements of electron temperature and density in the near-field plume of a Hall thruster were performed using a custom built laser Thomson scattering diagnostic. Laser measurements were processed using a maximum likelihood estimation method and results were compared to conventional electrostatic double probe measurements performed at the same thruster conditions. Electron temperature was found to range from approximately 1 – 40 eV and density ranged from approximately 1.0 x 1017 m-3 to 1.3 x 1018 m-3 over discharge voltages from 250 to 450 V and mass flow rates of 40 to 80 SCCM using xenon propellant.

Computational study of internal and external condensing flows and experimental synthesis to investigate their attainability and stability in ground-based and space-based environments

This doctoral thesis presents the computational work and synthesis with experiments for internal (tube and channel geometries) as well as external (flow of a pure vapor over a horizontal plate) condensing flows. The computational work obtains accurate numerical simulations of the full two dimensional governing equations for steady and unsteady condensing flows in gravity/0g environments. This doctoral work investigates flow features, flow regimes, attainability issues, stability issues, and responses to boundary fluctuations for condensing flows in different flow situations. This research finds new features of unsteady solutions of condensing flows; reveals interesting differences in gravity and shear driven situations; and discovers novel boundary condition sensitivities of shear driven internal condensing flows. Synthesis of computational and experimental results presented here for gravity driven in-tube flows lays framework for the future two-phase component analysis in any thermal system. It is shown for both gravity and shear driven internal condensing flows that steady governing equations have unique solutions for given inlet pressure, given inlet vapor mass flow rate, and fixed cooling method for condensing surface. But unsteady equations of shear driven internal condensing flows can yield different “quasi-steady” solutions based on different specifications of exit pressure (equivalently exit mass flow rate) concurrent to the inlet pressure specification. This thesis presents a novel categorization of internal condensing flows based on their sensitivity to concurrently applied boundary (inlet and exit) conditions. The computational investigations of an external shear driven flow of vapor condensing over a horizontal plate show limits of applicability of the analytical solution. Simulations for this external condensing flow discuss its stability issues and throw light on flow regime transitions because of ever-present bottom wall vibrations. It is identified that laminar to turbulent transition for these flows can get affected by ever present bottom wall vibrations. Detailed investigations of dynamic stability analysis of this shear driven external condensing flow result in the introduction of a new variable, which characterizes the ratio of strength of the underlying stabilizing attractor to that of destabilizing vibrations. Besides development of CFD tools and computational algorithms, direct application of research done for this thesis is in effective prediction and design of two-phase components in thermal systems used in different applications. Some of the important internal condensing flow results about sensitivities to boundary fluctuations are also expected to be applicable to flow boiling phenomenon. Novel flow sensitivities discovered through this research, if employed effectively after system level analysis, will result in the development of better control strategies in ground and space based two-phase thermal systems.

Length of the annular regime for condensing flows inside a horizontal channel - the experimental determination of its values and its trends

The experiments observe and measure the length of the annular regime in fully condensing quasi-steady (steady-in-the-mean) flows of pure FC-72 vapor in a horizontal condenser (rectangular cross-section of 2 mm height, 15 mm width, and 1 m length). The sides and top of the duct are made of clear plastic that allows flow visualization. The experimental system in which this condenser is used is able to control and achieve different quasi-steady mass flow rates, inlet pressures, and wall cooling conditions (by adjustment of the temperature and flow rate of the cooling water flowing underneath the condensing-plate). The reported correlations and measurements for the annular length are also vital information for determining the length of the annular regime and proposing extended correlation (covering many vapors and a larger parameter set than the experimentally reported version here) by ongoing independent modeling and computational simulation approach.