Investigations of Cloud Microphysical Response to Mixing Using Digital Holography

Cloud edge mixing plays an important role in the life cycle and development of clouds. Entrainment of subsaturated air affects the cloud at the microscale, altering the number density and size distribution of its droplets. The resulting effect is determined by two timescales: the time required for the mixing event to complete, and the time required for the droplets to adjust to their new environment. If mixing is rapid, evaporation of droplets is uniform and said to be homogeneous in nature. In contrast, slow mixing (compared to the adjustment timescale) results in the droplets adjusting to the transient state of the mixture, producing an inhomogeneous result. Studying this process in real clouds involves the use of airborne optical instruments capable of measuring clouds at the `single particle' level. Single particle resolution allows for direct measurement of the droplet size distribution. This is in contrast to other `bulk' methods (i.e. hot-wire probes, lidar, radar) which measure a higher order moment of the distribution and require assumptions about the distribution shape to compute a size distribution. The sampling strategy of current optical instruments requires them to integrate over a path tens to hundreds of meters to form a single size distribution. This is much larger than typical mixing scales (which can extend down to the order of centimeters), resulting in difficulties resolving mixing signatures. The Holodec is an optical particle instrument that uses digital holography to record discrete, local volumes of droplets. This method allows for statistically significant size distributions to be calculated for centimeter scale volumes, allowing for full resolution at the scales important to the mixing process. The hologram also records the three dimensional position of all particles within the volume, allowing for the spatial structure of the cloud volume to be studied. Both of these features represent a new and unique view into the mixing problem. In this dissertation, holographic data recorded during two different field projects is analyzed to study the mixing structure of cumulus clouds. Using Holodec data, it is shown that mixing at cloud top can produce regions of clear but humid air that can subside down along the edge of the cloud as a narrow shell, or advect down shear as a `humid halo'. This air is then entrained into the cloud at lower levels, producing mixing that appears to be very inhomogeneous. This inhomogeneous-like mixing is shown to be well correlated with regions containing elevated concentrations of large droplets. This is used to argue in favor of the hypothesis that dilution can lead to enhanced droplet growth rates. I also make observations on the microscale spatial structure of observed cloud volumes recorded by the Holodec.

Charge induced enhancement of adsorption for hydrogen storage materials

The rising concerns about environmental pollution and global warming have facilitated research interest in hydrogen energy as an alternative energy source. To apply hydrogen for transportations, several issues have to be solved, within which hydrogen storage is the most critical problem. Lots of materials and devices have been developed; however, none is able to meet the DOE storage target. The primary issue for hydrogen physisorption is a weak interaction between hydrogen and the surface of solid materials, resulting negligible adsorption at room temperature. To solve this issue, there is a need to increase the interaction between the hydrogen molecules and adsorbent surface. In this study, intrinsic electric dipole is investigated to enhance the adsorption energy. The results from the computer simulation of single ionic compounds with hydrogen molecules to form hydrogen clusters showed that electrical charge of substances plays an important role in generation of attractive interaction with hydrogen molecules. In order to further examine the effects of static interaction on hydrogen adsorption, activated carbon with a large surface area was impregnated with various ionic salts including LiCl, NaCl, KCl, KBr, and NiCl and their performance for hydrogen storage was evaluated by using a volumetric method. Corresponding computer simulations have been carried out by using DFT (Density Functional Theory) method combined with point charge arrays. Both experimental and computational results prove that the adsorption capacity of hydrogen and its interaction with the solid materials increased with electrical dipole moment. Besides the intrinsic dipole, an externally applied electric field could be another means to enhance hydrogen adsorption. Hydrogen adsorption under an applied electric field was examined by using porous nickel foil as electrodes. Electrical signals showed that adsorption capacity increased with the increasing of gas pressure and external electric voltage. Direct measurement of the amount of hydrogen adsorption was also carried out with porous nickel oxides and magnesium oxides using the piezoelectric material PMN-PT as the charge supplier due to the pressure. The adsorption enhancement from the PMN-PT generated charges is obvious at hydrogen pressure between 0 and 60 bars, where the hydrogen uptake is increased at about 35% for nickel oxide and 25% for magnesium oxide. Computer simulation reveals that under the external electric field, the electron cloud of hydrogen molecules is pulled over to the adsorbent site and can overlap with the adsorbent electrons, which in turn enhances the adsorption energy Experiments were also carried out to examine the effects of hydrogen spillover with charge induced enhancement. The results show that the overall storage capacity in nickel oxide increased remarkably by a factor of 4.

Reynolds-stress turbulence model in the KIVA code for engine simulation

A Reynolds-Stress Turbulence Model has been incorporated with success into the KIVA code, a computational fluid dynamics hydrocode for three-dimensional simulation of fluid flow in engines. The newly implemented Reynolds-stress turbulence model greatly improves the robustness of KIVA, which in its original version has only eddy-viscosity turbulence models. Validation of the Reynolds-stress turbulence model is accomplished by conducting pipe-flow and channel-flow simulations, and comparing the computed results with experimental and direct numerical simulation data. Flows in engines of various geometry and operating conditions are calculated using the model, to study the complex flow fields as well as confirm the model’s validity. Results show that the Reynolds-stress turbulence model is able to resolve flow details such as swirl and recirculation bubbles. The model is proven to be an appropriate choice for engine simulations, with consistency and robustness, while requiring relatively low computational effort.

Dynamic modeling, simulation and control design of a parafoil-payload system for ship launched aerial delivery system (SLADS)

The objective of this research was to develop a high-fidelity dynamic model of a parafoilpayload system with respect to its application for the Ship Launched Aerial Delivery System (SLADS). SLADS is a concept in which cargo can be transfered from ship to shore using a parafoil-payload system. It is accomplished in two phases: An initial towing phase when the glider follows the towing vessel in a passive lift mode and an autonomous gliding phase when the system is guided to the desired point. While many previous researchers have analyzed the parafoil-payload system when it is released from another airborne vehicle, limited work has been done in the area of towing up the system from ground or sea. One of the main contributions of this research was the development of a nonlinear dynamic model of a towed parafoil-payload system. After performing an extensive literature review of the existing methods of modeling a parafoil-payload system, a five degree-of-freedom model was developed. The inertial and geometric properties of the system were investigated to predict accurate results in the simulation environment. Since extensive research has been done in determining the aerodynamic characteristics of a paraglider, an existing aerodynamic model was chosen to incorporate the effects of air flow around the flexible paraglider wing. During the towing phase, it is essential that the parafoil-payload system follow the line of the towing vessel path to prevent an unstable flight condition called ‘lockout’. A detailed study of the causes of lockout, its mathematical representation and the flight conditions and the parameters related to lockout, constitute another contribution of this work. A linearized model of the parafoil-payload system was developed and used to analyze the stability of the system about equilibrium conditions. The relationship between the control surface inputs and the stability was investigated. In addition to stability of flight, one more important objective of SLADS is to tow up the parafoil-payload system as fast as possible. The tension in the tow cable is directly proportional to the rate of ascent of the parafoil-payload system. Lockout instability is more favorable when tow tensions are large. Thus there is a tradeoff between susceptibility to lockout and rapid deployment. Control strategies were also developed for optimal tow up and to maintain stability in the event of disturbances.

Three dimensional finite element simulation of polymer melting and flow in a single-screw extruder : optimization of screw channel geometry

Single-screw extrusion is one of the widely used processing methods in plastics industry, which was the third largest manufacturing industry in the United States in 2007 [5]. In order to optimize the single-screw extrusion process, tremendous efforts have been devoted for development of accurate models in the last fifty years, especially for polymer melting in screw extruders. This has led to a good qualitative understanding of the melting process; however, quantitative predictions of melting from various models often have a large error in comparison to the experimental data. Thus, even nowadays, process parameters and the geometry of the extruder channel for the single-screw extrusion are determined by trial and error. Since new polymers are developed frequently, finding the optimum parameters to extrude these polymers by trial and error is costly and time consuming. In order to reduce the time and experimental work required for optimizing the process parameters and the geometry of the extruder channel for a given polymer, the main goal of this research was to perform a coordinated experimental and numerical investigation of melting in screw extrusion. In this work, a full three-dimensional finite element simulation of the two-phase flow in the melting and metering zones of a single-screw extruder was performed by solving the conservation equations for mass, momentum, and energy. The only attempt for such a three-dimensional simulation of melting in screw extruder was more than twenty years back. However, that work had only a limited success because of the capability of computers and mathematical algorithms available at that time. The dramatic improvement of computational power and mathematical knowledge now make it possible to run full 3-D simulations of two-phase flow in single-screw extruders on a desktop PC. In order to verify the numerical predictions from the full 3-D simulations of two-phase flow in single-screw extruders, a detailed experimental study was performed. This experimental study included Maddock screw-freezing experiments, Screw Simulator experiments and material characterization experiments. Maddock screw-freezing experiments were performed in order to visualize the melting profile along the single-screw extruder channel with different screw geometry configurations. These melting profiles were compared with the simulation results. Screw Simulator experiments were performed to collect the shear stress and melting flux data for various polymers. Cone and plate viscometer experiments were performed to obtain the shear viscosity data which is needed in the simulations. An optimization code was developed to optimize two screw geometry parameters, namely, screw lead (pitch) and depth in the metering section of a single-screw extruder, such that the output rate of the extruder was maximized without exceeding the maximum temperature value specified at the exit of the extruder. This optimization code used a mesh partitioning technique in order to obtain the flow domain. The simulations in this flow domain was performed using the code developed to simulate the two-phase flow in single-screw extruders.

Implementation of a phenomenological evaporation model into a porous network simulation for water management in low temperature fuel cells

A phenomenological transition film evaporation model was introduced to a pore network model with the consideration of pore radius, contact angle, non-isothermal interface temperature, microscale fluid flows and heat and mass transfers. This was achieved by modeling the transition film region of the menisci in each pore throughout the porous transport layer of a half-cell polymer electrolyte membrane (PEM) fuel cell. The model presented in this research is compared with the standard diffusive fuel cell modeling approach to evaporation and shown to surpass the conventional modeling approach in terms of predicting the evaporation rates in porous media. The current diffusive evaporation models used in many fuel cell transport models assumes a constant evaporation rate across the entire liquid-air interface. The transition film model was implemented into the pore network model to address this issue and create a pore size dependency on the evaporation rates. This is accomplished by evaluating the transition film evaporation rates determined by the kinetic model for every pore containing liquid water in the porous transport layer (PTL). The comparison of a transition film and diffusive evaporation model shows an increase in predicted evaporation rates for smaller pore sizes with the transition film model. This is an important parameter when considering the micro-scaled pore sizes seen in the PTL and becomes even more substantial when considering transport in fuel cells containing an MPL, or a large variance in pore size. Experimentation was performed to validate the transition film model by monitoring evaporation rates from a non-zero contact angle water droplet on a heated substrate. The substrate was a glass plate with a hydrophobic coating to reduce wettability. The tests were performed at a constant substrate temperature and relative humidity. The transition film model was able to accurately predict the drop volume as time elapsed. By implementing the transition film model to a pore network model the evaporation rates present in the PTL can be more accurately modeled. This improves the ability of a pore network model to predict the distribution of liquid water and ultimately the level of flooding exhibited in a PTL for various operating conditions.

In-situ measurement and characterization of cloud particles using digital in-line holography

Satellite measurement validations, climate models, atmospheric radiative transfer models and cloud models, all depend on accurate measurements of cloud particle size distributions, number densities, spatial distributions, and other parameters relevant to cloud microphysical processes. And many airborne instruments designed to measure size distributions and concentrations of cloud particles have large uncertainties in measuring number densities and size distributions of small ice crystals. HOLODEC (Holographic Detector for Clouds) is a new instrument that does not have many of these uncertainties and makes possible measurements that other probes have never made. The advantages of HOLODEC are inherent to the holographic method. In this dissertation, I describe HOLODEC, its in-situ measurements of cloud particles, and the results of its test flights. I present a hologram reconstruction algorithm that has a sample spacing that does not vary with reconstruction distance. This reconstruction algorithm accurately reconstructs the field to all distances inside a typical holographic measurement volume as proven by comparison with analytical solutions to the Huygens-Fresnel diffraction integral. It is fast to compute, and has diffraction limited resolution. Further, described herein is an algorithm that can find the position along the optical axis of small particles as well as large complex-shaped particles. I explain an implementation of these algorithms that is an efficient, robust, automated program that allows us to process holograms on a computer cluster in a reasonable time. I show size distributions and number densities of cloud particles, and show that they are within the uncertainty of independent measurements made with another measurement method. The feasibility of another cloud particle instrument that has advantages over new standard instruments is proven. These advantages include a unique ability to detect shattered particles using three-dimensional positions, and a sample volume size that does not vary with particle size or airspeed. It also is able to yield two-dimensional particle profiles using the same measurements.

Long-Range Pollution Transport: Trans-Atlantic Mechanisms and Lagrangian Modeling Methods

Over the past several decades, it has become apparent that anthropogenic activities have resulted in the large-scale enhancement of the levels of many trace gases throughout the troposphere. More recently, attention has been given to the transport pathway taken by these emissions as they are dispersed throughout the atmosphere. The transport pathway determines the physical characteristics of emissions plumes and therefore plays an important role in the chemical transformations that can occur downwind of source regions. For example, the production of ozone (O3) is strongly dependent upon the transport its precursors undergo. O3 can initially be formed within air masses while still over polluted source regions. These polluted air masses can experience continued O3 production or O3 destruction downwind, depending on the air mass's chemical and transport characteristics. At present, however, there are a number of uncertainties in the relationships between transport and O3 production in the North Atlantic lower free troposphere. The first phase of the study presented here used measurements made at the Pico Mountain observatory and model simulations to determine transport pathways for US emissions to the observatory. The Pico Mountain observatory was established in the summer of 2001 in order to address the need to understand the relationships between transport and O3 production. Measurements from the observatory were analyzed in conjunction with model simulations from the Lagrangian particle dispersion model (LPDM), FLEX-PART, in order to determine the transport pathway for events observed at the Pico Mountain observatory during July 2003. A total of 16 events were observed, 4 of which were analyzed in detail. The transport time for these 16 events varied from 4.5 to 7 days, while the transport altitudes over the ocean ranged from 2-8 km, but were typically less than 3 km. In three of the case studies, eastward advection and transport in a weak warm conveyor belt (WCB) airflow was responsible for the export of North American emissions into the FT, while transport in the FT was governed by easterly winds driven by the Azores/Bermuda High (ABH) and transient northerly lows. In the fourth case study, North American emissions were lofted to 6-8 km in a WCB before being entrained in the same cyclone's dry airstream and transported down to the observatory. The results of this study show that the lower marine FT may provide an important transport environment where O3 production may continue, in contrast to transport in the marine boundary layer, where O3 destruction is believed to dominate. The second phase of the study presented here focused on improving the analysis methods that are available with LPDMs. While LPDMs are popular and useful for the analysis of atmospheric trace gas measurements, identifying the transport pathway of emissions from their source to a receptor (the Pico Mountain observatory in our case) using the standard gridded model output, particularly during complex meteorological scenarios can be difficult can be difficult or impossible. The transport study in phase 1 was limited to only 1 month out of more than 3 years of available data and included only 4 case studies out of the 16 events specifically due to this confounding factor. The second phase of this study addressed this difficulty by presenting a method to clearly and easily identify the pathway taken by only those emissions that arrive at a receptor at a particular time, by combining the standard gridded output from forward (i.e., concentrations) and backward (i.e., residence time) LPDM simulations, greatly simplifying similar analyses. The ability of the method to successfully determine the source-to-receptor pathway, restoring this Lagrangian information that is lost when the data are gridded, is proven by comparing the pathway determined from this method with the particle trajectories from both the forward and backward models. A sample analysis is also presented, demonstrating that this method is more accurate and easier to use than existing methods using standard LPDM products. Finally, we discuss potential future work that would be possible by combining the backward LPDM simulation with gridded data from other sources (e.g., chemical transport models) to obtain a Lagrangian sampling of the air that will eventually arrive at a receptor.

PARAMETRIC STUDY OF REAXFF SIMULATION PARAMETERS FOR MOLECULAR DYNAMICS MODELING OF REACTIVE CARBON GASES

Abstract The development of innovative carbon-based materials can be greatly facilitated by molecular modeling techniques. Although the Reax Force Field (ReaxFF) can be used to simulate the chemical behavior of carbon-based systems, the simulation settings required for accurate predictions have not been fully explored. Using the ReaxFF, molecular dynamics (MD) simulations are used to simulate the chemical behavior of pure carbon and hydrocarbon reactive gases that are involved in the formation of carbon structures such as graphite, buckyballs, amorphous carbon, and carbon nanotubes. It is determined that the maximum simulation time step that can be used in MD simulations with the ReaxFF is dependent on the simulated temperature and selected parameter set, as are the predicted reaction rates. It is also determined that different carbon-based reactive gases react at different rates, and that the predicted equilibrium structures are generally the same for the different ReaxFF parameter sets, except in the case of the predicted formation of large graphitic structures with the Chenoweth parameter set under specific conditions.