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Laboratory Simulations of Micrometeoroid Ablation Laboratory Simulations of Micrometeoroid Ablation by Evan Williamson Thomas B.S., Engineering Physics, magna cum laude 2010 M.S., Physics, 2015 University of Colorado, Boulder, CO A thesis submitted to the Faculty of the Graduate School of the University of Colorado in partial fulfillment of the requirements for the degree of Doctor of Philosophy Department of Physics 2017 This thesis entitled: Laboratory Simulations of Micrometeoroid Ablation written by Evan Williamson Thomas has been approved for the Department of Physics Prof. Tobin Munsat Prof. Mih´alyHor´anyi Date The final copy of this thesis has been examined by the signatories, and we find that both the content and the form meet acceptable presentation standards of scholarly work in the above mentioned discipline. iii Thomas, Evan Williamson (Ph.D., Physics) Laboratory Simulations of Micrometeoroid Ablation Thesis directed by Prof. Tobin Munsat Each day, several tons of meteoric material enters Earth's atmosphere, the majority of which consist of small dust particles (micrometeoroids) that completely ablate at high altitudes. The dust input has been suggested to play a role in a variety of phenomena including: layers of metal atoms and ions, nucleation of noctilucent clouds, effects on stratospheric aerosols and ozone chemistry, and the fertilization of the ocean with bio-available iron. Furthermore, a correct understanding of the dust input to the Earth provides constraints on inner solar system dust models. Various methods are used to measure the dust input to the Earth including satellite detectors, radar, lidar, rocket-borne detectors, ice core and deep-sea sediment analysis. However, the best way to interpret each of these measurements is uncertain, which leads to large uncertainties in the total dust input. To better understand the ablation process, and thereby reduce uncertainties in micromete- oroid ablation measurements, a facility has been developed to simulate the ablation of micromete- oroids in laboratory conditions. An electrostatic dust accelerator is used to accelerate iron particles to relevant meteoric velocities (10-70 km/s). The particles are then introduced into a chamber pres- surized with a target gas, and they partially or completely ablate over a short distance. An array of diagnostics then measure, with timing and spatial resolution, the charge and light that is generated in the ablation process. In this thesis, we present results from the newly developed ablation facility. The ionization coefficient, an important parameter for interpreting meteor radar measurements, is measured for various target gases. Furthermore, experimental ablation measurements are compared to predic- tions from commonly used ablation models. In light of these measurements, implications to the broader context of meteor ablation are discussed. Dedication To my parents, for offering love and support in all my endeavors. v Acknowledgements I would like to thank my advisor, Tobin Munsat, for all of his support through this process. I would also like to acknowledge Profs. Zoltan Sternovsky and Mih´alyHor´anyi for their many insights on this project. Additionally, I offer my gratitude to the entire laboratory staff at IMPACT for their assistance with running the experiments and maintaing the accelerator. This research was funded by the National Aeronautics and Space Administration and the Solar System Exploration Research Virtual Institute. vi Contents Chapter 1 Introduction 1 1.1 Interplanetary Dust Particles . 1 1.2 Radar Measurements of Meteoroids . 4 1.3 Scientific Motivation & Science Questions . 6 1.4 Previous Laboratory Ablation Experiments . 9 1.5 Ablation in Laboratory Conditions . 11 1.6 Thesis Outline . 12 2 Dust Accelerator Facility 13 2.1 Dust Accelerator Overview . 13 2.1.1 Dust Source . 16 2.1.2 Accelerating Column and Focusing . 17 2.1.3 Beamline Dust Detectors . 20 2.1.4 PSU & Deflection Plates . 23 2.1.5 Accelerator Data Handling . 24 2.2 FPGA Particle Selection . 26 2.2.1 Introduction & Motivation . 26 2.2.2 Filter Design . 27 2.2.3 Algorithm Overview . 33 vii 2.2.4 State Machine . 35 2.2.5 Hardware Implementation . 38 2.2.6 FPGA Results . 39 2.3 Summary . 42 3 Experimental Design 43 3.1 Design Overview . 43 3.2 Differential Pumping . 45 3.3 Ablation Chamber Overview . 47 3.4 Charge Collection CSA Design . 49 3.5 Optical Setup . 50 3.6 Data Acquisition . 52 3.7 Experimental Data Examples . 54 3.7.1 Charge Measurements . 54 3.7.2 Light Measurements . 56 3.8 Summary . 58 4 Modeling Support 59 4.1 Ablation Models . 59 4.1.1 CM Model . 60 4.1.2 SECAM . 68 4.2 Collection Efficiency . 80 4.3 Electron Impact Ionization . 84 4.4 Summary . 87 5 Ionization Coefficient Measurements 88 5.1 Methodology . 88 5.2 Ionization Coefficient Analytical Theory . 92 viii 5.3 Results . 94 5.4 Discussion . 98 5.5 Summary and Future Work . 102 6 Ablation Model Experimental Investigation 103 6.1 Deceleration . 103 6.1.1 Deceleration - Methodology . 103 6.1.2 Deceleration - Results . 106 6.2 Mass Loss Via Charge Collection . 116 6.2.1 Mass Loss - Methodology . 116 6.2.2 Mass Loss - Results . 117 6.3 Discussion . 121 6.4 Summary and Future Work . 122 7 Conclusion 124 7.1 Ionization Coefficient . 124 7.2 Ablation Models . 125 7.3 Future Work . 126 Bibliography 127 Appendix A Publications 134 ix Tables Table 1.1 Current global IDP mass input rates to the Earth. 8 2.1 A list of the sensitivities of the CSA circuits on the beamline dust detectors. 21 2.2 Summary of the performance differences between the FPGA system and the analog PSU. Each system was running in parallel, but the FPGA detected many more particles. The percent difference column gives the percentage that the respective system missed of the other system's dataset. 41 4.1 Coefficient values for the vapor pressure equations for the solid and liquid phase of iron. Reproduced from [2]. 65 4.2 Monte Carlo results of ion spreading in the ablation chamber run at 100 V bias between the top and bottom ablation plates. The displacement is the center value of the Gaussian, while σ is the standard deviation. 84 5.1 The fit parameters used in Figure 5.4. The coefficient (b) and exponent (α) values, and relevant velocity ranges for the power law fits to the data from this experiment for each gas are shown. The parameter c is the least-squares best fit of the parameter in the Jones [45] integral equation (Equations 5.5 and 5.8). The calculated threshold velocity, v0 (Equation 5.9) for each gas is the lowest meteor velocity which can produce ionization. 97 x 6.1 Best fit deceleration results of SECAM and CM for Ar. The units of aexp and amod 2 are µm/µs and aratio is defined as aexp=amod. 114 6.2 Best fit deceleration results of SECAM and CM for O2. The units of aexp and amod 2 are µm/µs and aratio is defined as aexp=amod. 115 xi Figures Figure 1.1 A diagram showing an example temperature profile of the atmosphere from 0 to 130 km, along with the associated atmospheric layers. The region where meteoroids typi- cally ablate is labeled. Source: http://http://www.srh.noaa.gov/srh/jetstream/atmos/layers.html. 2 1.2 Mass influx (per mass decade) as a function of particle mass. The huge impactors only contribute a significant amount of mass on geological timescales. Reproduced from [71]. 4 2.1 A schematic of the IMPACT dust accelerator. The accelerator contains a dust source, Einzel lens focusing system, a high-voltage accelerating column, three dust detec- tors, a particle selection unit (PSU), deflection plates, and a target chamber. The accelerating column consists of potential rings which run down the acceleration tube and create a uniform accelerating electric field. 14 2.2 A representative particle distribution from the accelerator. There is a large dynamic range of masses (8 orders of magnitude) and velocities (2 orders of magnitude) that the accelerator produces. 15 xii 2.3 A schematic of the 20 kV dust source. The reservoir holds the conducting dust and is pulsed between 0-20 kV relative to the extraction plate. The needle is held a fixed voltage, which is set to the maximum of the reservoir voltage. The dust becomes slightly negatively charged by the pulsing reservoir and begins to levitate. The dust becomes charged positively when it contacts the needle. The charged dust is then accelerated by the electric field which exists between the needle and the extraction plate and is ejected through the pinholes. Reproduced from [81]. 16 2.4 A schematic showing the charging mechanism for the Pelletron. The charging mech- anism is induction-based where the inductor/supressor creates an electric field be- tween them and the grounded pulley. The pulley is conducting such that when a chain metal pellet is touching the pulley, it is one grounded conductor. Looking at the inductor side, as a pellet moves into the electric field between the inductor and the pulley, a charge separation occurs where negative charge is pushed onto the pulley. Therefore, as the pellet moves off of the pulley, but is still in the electric field of the inductor, it gains a positive charge. The chain then transports that chrage to the terminal where the charge is pulled off by the pickoff pulleys. Source: http://www.pelletron.com/charging.htm . 18 2.5 Two SIMION simulations of the dust source, Einzel lens, and accelerating tube entrace. In the top panel (a), the Einzel lens is at 0 V, which produces a diverging beam in the accelerating tube. In the bottom panel (b), the Einzel lens is at 10 kV, which collimates the beam.
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