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A dissertation submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy

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Consequently, a total amount of such large dust particles detected by the ALADDIN measurement is more than 10 times that of previous in situ dust detectors. Thus, the applicability of ALADDIN for measuring dust particles ≥10 μm in size within Earth orbit was verified.

Debris Disks

INTRODUCTION

As the dust particles approach the Earth's external MMRs, a fraction of the particles are trapped in each resonance ratio. As they pass through interplanetary space, dust particles are subjected to mutual dust-dust collisions.

Fig. 1.2. The results of numerical calculation showing the orbital evolution of 12-µm-sized dust particles spiraling towards the Sun under the PR effect (Dermott et al., 1994)
Fig. 1.2. The results of numerical calculation showing the orbital evolution of 12-µm-sized dust particles spiraling towards the Sun under the PR effect (Dermott et al., 1994)

INTRODUCTION collisions

Solar System Dust Disks as References to Debris Disks

In situ dust impact detection is a more promising option to reveal the fine structure and size distribution within the dust disk in interplanetary space. In situ dust detectors orbiting the earth contributed to determining the size distribution of dust entering the Earth (e.g., Grün et al., 1985).

Fig. 1.3. Model of circumsolar dust ring around Earth’s orbit composed of asteroidal dust particles (Dermott et al., 1994).
Fig. 1.3. Model of circumsolar dust ring around Earth’s orbit composed of asteroidal dust particles (Dermott et al., 1994).

Objectives and content of the thesis

In this chapter, we will review the results and limitations of previous optical observations, in-situ measurements and dust distribution models within the Earth's orbit.

Optical Observations for Dust Distribution within 1 AU from the Sun

  • The Helios Photometers

In the following, a few examples of the optical observations within 1 AU from the Sun are reviewed. The spatial number density of interplanetary dust calculated from the luminosity-density conversion scheme is proportional to r−1.3, r being the radial distance from the Sun, as shown in Fig. 2.1.

PAST OBSERVATIONS, MEASUREMENTS, AND DISTRIBUTION MODELS OF DUST INSIDE THE EARTH’S ORBIT

It is virtually impossible for these effects to be produced by stars passing through the photometer's field of view. 7. The increase in brightness is seen with Helios A in sector 12 of the photometer looking ≈30◦ during the outgoing transit of Venus. superimposed on a ≈4 S10 basic zodiacal luminosity similar to that seen in Figs.

Observation results and dust distribution model

Discussion

1. Zodiacal brightness (upper curve) and reduced brightness (lower curve) as seen by the 90◦ photometer on Helios B in V during the inbound transit of Venus in March 1977. The arrow indicates the position of Helios B during the inbound transit of Venus.

Results

  • The Clementine Star Tracker Camera
  • The STEREO Imager
  • In-situ measurements for Dust Distribution within 1 AU from the Sunfrom the Sun
    • The Helios 1 Dust Detector
    • The Galileo Dust Detection System
    • The Cassini Cosmic Dust Analyzer
  • PVDF-Based Dust Detectors
    • Polyvinylidene Fluoride (PVDF)

Schematic of the Helios spacecraft installed with the dust detector and spacecraft orbit (Grün et al., 1980). The photograph of the sensor and electronics box of the Galileo Dust Detection System (Grün et al., 1992).

FIG. 5. A mosaic of seven fields of the inner zodiacal light observed by the Clementine star tracker camera
FIG. 5. A mosaic of seven fields of the inner zodiacal light observed by the Clementine star tracker camera

THE ALADDIN DUST DETECTOR

  • Theory of Charge Production from PVDF at Hypervelocity Impacts and Nanosecond Laser Irradiation

THE ALADDIN DUST DETECTOR et al. (1989) have expressed the generated charge as a function of electrical properties of PVDF,

  • The Past PVDF-Based Dust Detectors
  • Configuration and Characteristics of ALADDIN onboard IKAROSIKAROS
  • Functional Sequence
  • Analog Signal Processing
  • Calibration Experiments
    • Van de Graa ff Dust Accelerator
    • Two-Stage Light Gas Gun
    • Nano-Second Pulsed Nd:YAG Laser Irradiation Experiment
  • ALADDIN Performance as an In-situ Dust Detector
    • Calibration Curve
    • Dynamic Mass-Velocity Range
  • Noise Screening and Data Extraction for Scientific Dis- cussion
    • Noise Screening

A pair of both sensors is installed on each of the 4 petals of the IKAROS sail membrane. Graphs are the results of 20-µm thick ALDN-S: silver particles at HIT (asterisk), carbon particles at HIT (empty square), and iron particles (empty triangle). Thus, from the LGG experiments, we were able to obtain the signal parameter of ALADDIN, which we consider as a function of impact conditions, such as particle mass and impact velocity.

The signals measured at the output (black) and input (grey) terminals of the voltage amplifier are shown. Experimental conditions and results of the nsPL experiments: run number (No), number of energy absorbers (n), average laser energy (Eavg), deviation of the nsPL energy (Edev), signal parameter of ALADDIN (Is) and peak amplitude of the output signal (V). Finally, we estimate that the calibration law for ALADDIN can be empirically formulated as

In the laboratory calibration tests, we focused only on the analog response of the ALADDIN electronics to high-velocity microparticle impacts. Therefore, we investigated the probabilistic effect due to the sampling rate of the ALADDIN electronics signal.

Fig. 3.3. Comparison of sensor area of various PVDF-based dust detectors. The specific values of area from DUCMA to ALADDIN are 0.0075 m 2 (Simpson et al., 1986), 0.006 m 2 (Srama et al., 2004), 0.022 m 2 (Tuzzolino et al., 2003), 0.0576 m 2 (Tuzzolino et
Fig. 3.3. Comparison of sensor area of various PVDF-based dust detectors. The specific values of area from DUCMA to ALADDIN are 0.0075 m 2 (Simpson et al., 1986), 0.006 m 2 (Srama et al., 2004), 0.022 m 2 (Tuzzolino et al., 2003), 0.0576 m 2 (Tuzzolino et

NOISE SCREENING AND REDUCTION OF THE ALADDIN SPACE DATA

NOISE SCREENING AND REDUCTION OF THE ALADDIN SPACE DATA The specific cause of these crosstalk noise has not been confirmed by laboratory simulations,

  • Data Extraction for Scientific Discussion
  • NOISE SCREENING AND REDUCTION OF THE ALADDIN SP A CE D A T ANo.Target sensorProjectile materialProjectile mass (kg)Impact velocity (km/s)Ch.1Ch.2

NOISE SCREENING AND REDUCTION OF THE ALADDIN SPACE DATA The specific cause of this crosstalk noise has not been confirmed by laboratory simulations. Note that the dt values ​​of the marked channels were almost “9” and partially the error value “0”. To confirm the repeatability of the multi-flag events, we performed laboratory impact experiments.

It is difficult to prepare a complete set of spare parts for the ALDN-S flight and to reproduce the in-flight configuration on the deployed solar sail in the LGG vacuum chamber. Therefore, we only used a spare piece of large (20 µm thick) and small (9 µm thick) ALDN-S only for the shock target sensor and used a 10 cm × 10 cm PVDF sensor piece for a simplified, alternative dummy sensor. NOISE CHECKING AND REDUCTION OF ALADDIN SPACE DATA Comparing Table 4.3 and Table 4.4, we found that events with multiple flags on.

NOISE SCREENING AND REDUCTION OF THE ALADDIN SPACE DATA Comparing between Table 4.3 and Table 4.4, we found that the multi-flagged events at the

Since the large sensors did not present any signs of failure like Ch.2 (see Section 4.1.1), we assume that there is still some noise data on the small sensors. The event number on each small sensor that has one channel of maximum dV, including data with one flag. However, the event rates for channels 4 and 8 increase over time, which is not represented by any other channel.

These facts suggest that chapter 4 and chapter 8 have become "noisy" such as Ch.2 probably due to exposure to high temperature. The event rate of Ch.4 and Ch.8 along the heliocentric distance between 0.72 AU and 1.1 AU. The start of the measurement corresponds to the lower right point. The rate of Ch.4 in the first bin 0.72-0.8 AU fell to 0.

Fig. 4.3 shows the event number on each small sensor that have single channel of the maxi- maxi-mum dV including single-flagged data
Fig. 4.3 shows the event number on each small sensor that have single channel of the maxi- maxi-mum dV including single-flagged data

NOISE SCREENING AND REDUCTION OF THE ALADDIN SPACE DATA shows dV histogram of the single-flagged (filled black bar) and the multi-flagged (unfilled red

  • Thermal Degradation of PVDF

NOISE VIEW AND SPACE DATA REDUCTION ALADDIN shows the dV histogram of single (filled black bar) and multiple flags (unfilled red bar. Experimental conditions and results of an impact experiment with LGG to investigate the sensitivity of 156 °C-heated 20 µm ALDN-S. Sensor calibration curve, heated to 156 °C, passes through the average point of three experimental data of the sensor heated to 156 °C, which is obtained assuming the same slope of the 100◦C calibration curve.

If we consider the sensor temperature, T (◦C), as a function of this offset, we can obtain a calibration curve of the sensor heated to 180◦C, which can be the highest temperature ALDN-S can experience. Note that the confidence levels of these calibration curves at V = 4 V are quite ambiguous due to the lack of impact test data with 10 s-µm (m kg) projectiles. NOISE CHECKING AND DATA REDUCTION OF THE ALADDIN SPACE The detection sensitivity of the 180◦C sensor is debatable.

Fig. 4.5. dV histogram of the large sensors. As for the single-flagged (filled black bar) and the multi-flagged (unfilled red bar) data, maximum dV are shown
Fig. 4.5. dV histogram of the large sensors. As for the single-flagged (filled black bar) and the multi-flagged (unfilled red bar) data, maximum dV are shown

NOISE SCREENING AND REDUCTION OF THE ALADDIN SPACE DATA detection sensitivity of the 180 ◦ C sensor may be open to discuss

  • Sampling Probability

In addition to false detection, dV does not necessarily correspond to V, depending on the magnitude of the signal and the sampling time of the signal. The sum of the probabilities of each V corresponds to the detection probability shown in the figure. NOISE REVIEW AND REDUCTION OF SPACE DATA ALADDIN adV≥4 V for further scientific discussions of cosmic dust.

Fig. 4.9. The relation between V and detection probability.
Fig. 4.9. The relation between V and detection probability.
  • The ALADDIN Measurement Results and Its Interpretation

IKAROS membrane) and orbital element distribution of typical zodiacal dust particles (Hirai et al., 2014). The flux error of ALADDIN is much smaller than previous in-situ detectors. ALADDIN's highly accurate and precise flux shows a significant discrepancy compared to the standard model of the interplanetary dust flux at 1 AU, the Grün model (Grün et al., 1985).

The Grün model is an empirical mass (size) distribution of interplanetary dust particles based on in-situ flux measurement by Earth-orbiting satellites and crater counting of lunar samples (Grün et al., 1985). The extrapolation is based on Keplerian velocity and geometric concentration of number density (Eq. 18 in Grün et al., 1985). Note that the flux value of the Grün model in Fig. 5.1 has been corrected from the original value given in Grün et al. 1985), in which a factor of gravitational enhancement, 2, is considered.

NEW DUST DISTRIBUTION MODEL INSIDE THE EARTH’S ORBIT The ALADDIN flux shows significant higher flux than the Grün flux, even considering the

The detected size of dust particles by ALADDIN depends on the sensor temperature, i.e. the heliocentric distance. After its perihelion passage, the ALADDIN detected dust particles larger than ~67 µm, but there remains room for discussion (section 4.2). The flux of Helios can be calculated with measurement data of ≥1 µm due to the small sensor geometry (section 2.2.1).

Fig. 5.1. Flux comparison between (a) ALADDIN, (b) Helios, (c) Galileo, and Grün flux model
Fig. 5.1. Flux comparison between (a) ALADDIN, (b) Helios, (c) Galileo, and Grün flux model

NEW DUST DISTRIBUTION MODEL INSIDE THE EARTH’S ORBIT

  • Development of a New Hybrid Dust Distribution Model
    • Stark’s Mean Motion Resonances (MMRs) Model
    • Ishimoto’s Collisional Model
    • A New MMRs-Collisional Hybrid Model

7, the number density for masses 10−14g ~ 10−12g is about two orders of magnitude smaller than that of the IMF model. As a result, the hump in the number density distribution for particles with masses 10−12g ≤ m ≤ 10−7g becomes larger closer to the Sun. Despite the radial increase in dust production between 0.5AU and 1AU, the number density distribution for m≥ 10−5 is almost constant in case (C)-a.

This means that the number density distribution in this mass range remains constant if the substance input has the same radial dependence. On the other hand, an increase in the collision gain increases the number density for smaller particles. 7a – c. The calculated number density distribution for case (C)-a (top panel), case (C)-b (middle panel) and case (C)-c (bottom panel).

Fig. 5.3. Surface number density maps of 8 µm (upper left), 25 µm (upper right), 80 µm (bottom left), and 250 µm (bottom right) in diameter with 1 earth-mass planet orbiting at 1 AU (Stark and Kuchner, 2008).
Fig. 5.3. Surface number density maps of 8 µm (upper left), 25 µm (upper right), 80 µm (bottom left), and 250 µm (bottom right) in diameter with 1 earth-mass planet orbiting at 1 AU (Stark and Kuchner, 2008).
  • Azimuthal Variation of Interplanetary Dust Particles at 1 AU1 AU
  • Conclusions

Both the simulation results of the Stark model and the new hybrid model are compared with the in situ measured flux by the ALADDIN and the Grün model, which are based on in situ measurements around the Earth. The differential number density of in-situ measurements was calculated by the correlation between cumulative flux and differential number density presented in Grün et al. The in-situ measurement shows a significant difference between the opening and the rear clog by a factor of 12.6, while the difference estimated by the Stark model and our new model is a factor of 1.7 and 2.1, respectively.

Taking into account the uncertainty of the number density of the in situ measurements, in particular the large error of the Grün current, the difference could be at least 2.8. We compare the simulation density calculated using the Stark model and our new hybrid model with the in situ measurement density. The reduced ALADDIN data provides a 10-fold more accurate flux value for dust particles ≥10 µm in past in situ measurements.

Fig. 5.7. The trajectory of ALADDIN superimposed on the Stark 25-µm density map. The color scale represents relative number density (Stark and Kuchner, 2008).
Fig. 5.7. The trajectory of ALADDIN superimposed on the Stark 25-µm density map. The color scale represents relative number density (Stark and Kuchner, 2008).

CONCLUSIONS AND FUTURE WORK

  • Future Works

The VdG experiments at MPIK were supported by the exchange program of Center for Planetary Science (CPS) and the course-by-course education program of the Graduate University for Advanced Studies. The LGG experiments at UKC were supported by JAXA's Solar Power Sail Working Group and the Graduate University for Advanced Studies' course-by-course education program. Hypervelocity impact studies using the 2 MV Van de Graaff accelerator and the University of Kent's two-stage light gas cannon at Canterbury.

Clement Observations of the Zodiacal Light and Dust Content of the Inner Solar System. Microparticle impact calibration of the {INterplanetary} Space Array Large Area Dust Detectors (ALADDIN) aboard the {IKAROS} Cruise Solar Demonstrator. Modeling the number density distribution of interplanetary dust in the ecliptic plane within 5 AU from the Sun.

Figure 3. PACS 70 µm images of Vega and Fomalhaut along with their reference PSF stars, α Boo, and α Tau
Fig. 1.2. The results of numerical calculation showing the orbital evolution of 12-µm-sized dust particles spiraling towards the Sun under the PR effect (Dermott et al., 1994)
Fig. 1.3. Model of circumsolar dust ring around Earth’s orbit composed of asteroidal dust particles (Dermott et al., 1994).
Fig. 2.2. Radial dependence of spatial number density of interplanetary dust inferred by Helios 1 and Helios 2 observations (Leinert et al., 1983).
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