scholarly journals The residence-time of Jovian electrons in the inner heliosphere

2020 ◽  
Vol 642 ◽  
pp. A170
Author(s):  
A. Vogt ◽  
N. E. Engelbrecht ◽  
R. D. Strauss ◽  
B. Heber ◽  
A. Kopp ◽  
...  
Keyword(s):  
Residence Time ◽  
Propagation Model ◽  
Model Parameters ◽  
Propagation Time ◽  
Transport Parameters ◽  
Jovian Magnetosphere ◽  
In Situ Observations ◽  
Jovian Electrons ◽  
Inner Heliosphere

Context. Jovian electrons serve an important role in test-particle distribution in the inner heliosphere. They have been used extensively in the past to study the (diffusive) transport of cosmic rays in the inner heliosphere. With new limits on the Jovian source function, that is, the particle intensity just outside the Jovian magnetosphere, and a new set of in-situ observations at 1 AU for cases of both good and poor magnetic connection between the source and observer, we revisit some of these earlier simulations. Aims. We aim to find the optimal numerical set-up that can be used to simulate the propagation of 6 MeV Jovian electrons in the inner heliosphere. Using such a setup, we further aim to study the residence (propagation) times of these particles for different levels of magnetic connection between Jupiter and an observer at Earth (1 AU). Methods. Using an advanced Jovian electron propagation model based on the stochastic differential equation approach, we calculated the Jovian electron intensity for different model parameters. A comparison with observations leads to an optimal numerical setup, which was then used to calculate the so-called residence (propagation) times of these particles. Results. Through a comparison with in-situ observations, we were able to derive transport parameters that are appropriate for the study of the propagation of 6 MeV Jovian electrons in the inner heliosphere. Moreover, using these values, we show that the method of calculating the residence time applied in the existing literature is not suited to being interpreted as the propagation time of physical particles. This is due to an incorrect weighting of the probability distribution. We applied a new method, where the results from each pseudo-particle are weighted by its resulting phase-space density (i.e. the number of physical particles that it represents). We thereby obtained more reliable estimates for the propagation time.

In Situ Observations of Interplanetary Dust Variability in the Inner Heliosphere

2020 ◽  
Vol 892 (2) ◽  
pp. 115
Author(s):  
David M. Malaspina ◽  
Jamey R. Szalay ◽  
Petr Pokorný ◽  
Brent Page ◽  
Stuart D. Bale ◽  
...  
Keyword(s):  
Interplanetary Dust ◽  
In Situ Observations ◽  
Inner Heliosphere

scholarly journals MHD Modeling of the Background Solar Wind in the Inner Heliosphere From 0.1 to 5.5 AU: Comparison With In Situ Observations

Space Weather ◽  
2020 ◽  
Vol 18 (6) ◽  
Author(s):  
Y. X. Wang ◽  
X. C. Guo ◽  
C. Wang ◽  
V. Florinski ◽  
F. Shen ◽  
...  
Keyword(s):  
Solar Wind ◽  
Mhd Modeling ◽  
In Situ Observations ◽  
Inner Heliosphere

scholarly journals Theory of cosmic ray modulation

2008 ◽  
Vol 4 (S257) ◽  
pp. 429-438 ◽  
Author(s):  
Stefan E. S. Ferreira
Keyword(s):  
Magnetic Field ◽  
Three Dimensional ◽  
Cosmic Ray ◽  
Transport Parameters ◽  
Cosmic Ray Modulation ◽  
Field Lines ◽  
Jovian Electrons ◽  
Globally Distributed ◽  
The Magnetic Field ◽  
Inner Heliosphere

AbstractThis work aims to give a brief overview on the topic of cosmic ray modulation in the heliosphere. The heliosphere, heliospheric magnetic field, transport parameters and the transport equation together with modulation models, which solve this equation in various degree of complexity, are briefly discussed. Results from these models are then presented where first it is shown how cosmic rays are globally distributed in an asymmetrical heliosphere which results from the relative motion between the local interstellar medium and the Sun. Next the focus shifts to low-energy Jovian electrons. The intensities of these electrons, which originate from a point source in the inner heliosphere, exhibit a unique three-dimensional spiral structure where most of the particles are transported along the magnetic field lines. Time-dependent modulation is also discussed where it is shown how drift effects together with propagating diffusion barriers are responsible for modulation over a solar cycle.

scholarly journals TIER version 1.0: an open-source Topographically InformEd Regression (TIER) model to estimate spatial meteorological fields

2020 ◽  
Vol 13 (4) ◽  
pp. 1827-1843
Author(s):  
Andrew J. Newman ◽  
Martyn P. Clark
Keyword(s):  
Modular Design ◽  
Model Parameters ◽  
Complete Understanding ◽  
Methodological Choices ◽  
Terrain Attributes ◽  
Systematic Fashion ◽  
Uncertainty Estimates ◽  
Regression Framework ◽  
In Situ Observations

Abstract. This paper introduces the Topographically InformEd Regression (TIER) model, which uses terrain attributes in a regression framework to distribute in situ observations of precipitation and temperature to a grid. The framework enables our understanding of complex atmospheric processes (e.g., orographic precipitation) to be encoded into a statistical model in an easy-to-understand manner. TIER is developed in a modular fashion with key model parameters exposed to the user. This enables the user community to easily explore the impacts of our methodological choices made to distribute sparse, irregularly spaced observations to a grid in a systematic fashion. The modular design allows incorporating new capabilities in TIER. Intermediate processing variables are also output to provide a more complete understanding of the algorithm and any algorithmic changes. The framework also provides uncertainty estimates. This paper presents a brief model evaluation and demonstrates that the TIER algorithm is functioning as expected. Several variations in model parameters and changes in the distributed variables are described. A key conclusion is that seemingly small changes in a model parameter result in large changes to the final distributed fields and their associated uncertainty estimates.

scholarly journals TIER Version 1.0: An open-source Topographically InformEd Regression (TIER) model to estimate spatial meteorological fields

2019 ◽  
Author(s):  
Andrew J. Newman ◽  
Martyn P. Clark
Keyword(s):  
Modular Design ◽  
Model Parameters ◽  
Complete Understanding ◽  
Methodological Choices ◽  
Terrain Attributes ◽  
Systematic Fashion ◽  
Uncertainty Estimates ◽  
Regression Framework ◽  
In Situ Observations

Abstract. This paper introduces the Topographically InformEd Regression (TIER) model, which uses terrain attributes in a regression framework to distribute in situ observations of precipitation and temperature to a grid. The framework enables our understanding of complex atmospheric processes (e.g. orographic precipitation) to be encoded into a statistical model in an easy to understand manner. TIER is developed in a modular fashion with key model parameters exposed to the user. This enables the user community to easily explore the impacts of our methodological choices made to distribute sparse, irregularly spaced observations to a grid in a systematic fashion. The modular design allows incorporating new capabilities in TIER. Intermediate processing variables are also output to provide a more complete understanding of the algorithm and any algorithmic changes. The framework also provides uncertainty estimates. This paper presents a brief model evaluation and demonstrates that the TIER algorithm is functioning as expected. Several variations in model parameters and changes in the distributed variables are described. A key conclusion is that seemingly small changes in a model parameter result in large changes to the final distributed fields and their associated uncertainty estimates.

scholarly journals Jovian electrons in the inner heliosphere

2018 ◽  
Vol 613 ◽  
pp. A28 ◽  
Author(s):  
A. Vogt ◽  
B. Heber ◽  
A. Kopp ◽  
M. S. Potgieter ◽  
R. D. Strauss
Keyword(s):  
Numerical Models ◽  
Transport Processes ◽  
Source Spectrum ◽  
Accurate Estimation ◽  
Jovian Magnetosphere ◽  
Test Particles ◽  
Charged Particle Transport ◽  
Jovian Electrons ◽  
Pioneer 10 ◽  
Inner Heliosphere

Context. Since the Pioneer 10 flyby of Jupiter it has become well known that electrons of Jovian origin dominate the lower MeV range of charged energetic particles in the inner heliosphere. Aims. Because the Jovian source can be treated as point-like in numerical models, many attempts to investigate charged particle transport in the inner heliosphere have utilized Jovian electrons as test particles. The reliability of the derived parameters for convective and diffusive transport processes are therefore highly dependent on an accurate estimation of the Jovian source spectrum. In this study we aim to provide such an estimation. Methods. In this study we have proposed a new electron source spectrum, specified at the boundary of the Jovian magnetosphere, fitted to flyby measurements by Pioneer 10 and Ulysses, with a spectral shape also in agreement with measurements at Earth’s orbit by Ulysses, Voyager 1, ISEE and SOHO. Results. The proposed spectrum is consistent with all previous theoretical suggestions, but deviates considerably in the lower MeV range which was inaccessible to those studies.

Using In-Situ Juno Observations to Understand the Evolution of Interplanetary Coronal Mass Ejections Within 1 AU and Beyond

2020 ◽  
Author(s):  
Emma Davies ◽  
Robert Forsyth ◽  
Simon Good
Keyword(s):  
Coronal Mass Ejections ◽  
Flux Rope ◽  
General Shape ◽  
Interplanetary Coronal Mass Ejections ◽  
Sheath Region ◽  
In Situ Observations ◽  
Phase Data ◽  
Radial Evolution ◽  
Inner Heliosphere

<p>Understanding the evolution of interplanetary coronal mass ejections (ICMEs) as they propagate through the heliosphere is essential in forecasting space weather severity. Much of our knowledge of ICMEs has been gained using in-situ measurements from single spacecraft, although the increasing number of missions in the inner heliosphere has led to an increase in multi-spacecraft studies improving our understanding of the global structure of ICMEs. Whilst most such recent studies have focused on the inner heliosphere within 1 AU, Juno cruise phase data provides a new opportunity to study ICME evolution over greater distances. We present analysis of ICMEs observed in-situ both by Juno and at least one other spacecraft within 1 AU to investigate their evolution as they propagate through the heliosphere. Investigation of the sheath region and timing considerations between spacecraft allows for the general shape of the shock front to be reconstructed. Combining in-situ observations and results of flux rope fitting techniques determines the global picture of the ICME as it propagates. However, effects on in-situ observations due to radial evolution and due to the longitudinal separation between multi-spacecraft remain hard to separate. We note the importance of the interplanetary environment in which the ICME propagates and the need for caution in radial alignment studies.  </p>

In situ observations of electromigration induced void behavior

1995 ◽  
Vol 53 ◽  
pp. 244-245
Author(s):  
T. Marieb ◽  
J. C. Bravman ◽  
P. Flinn ◽  
D. Gardner ◽  
M. Madden
Keyword(s):  
Electron Microscopy ◽  
Void Nucleation ◽  
Plan View ◽  
Transmission Electron ◽  
Nucleation Sites ◽  
Microelectronics Industry ◽  
In Situ Observations ◽  
Backscatter Electron Detector ◽  
Voltage Scanning

Electromigration and stress voiding have been active areas of research in the microelectronics industry for many years. While accelerated testing of these phenomena has been performed for the last 25 years[1-2], only recently has the introduction of high voltage scanning electron microscopy (HVSEM) made possible in situ testing of realistic, passivated, full thickness samples at high resolution.With a combination of in situ HVSEM and post-testing transmission electron microscopy (TEM) , electromigration void nucleation sites in both normal polycrystalline and near-bamboo pure Al were investigated. The effect of the microstructure of the lines on the void motion was also studied.The HVSEM used was a slightly modified JEOL 1200 EX II scanning TEM with a backscatter electron detector placed above the sample[3]. To observe electromigration in situ the sample was heated and the line had current supplied to it to accelerate the voiding process. After testing lines were prepared for TEM by employing the plan-view wedge technique [6].

scholarly journals Two-Stage Water Jet Landing Point Prediction Model for Intelligent Water Shooting Robot

Sensors ◽  
2021 ◽  
Vol 21 (8) ◽  
pp. 2704
Author(s):  
Yunhan Lin ◽  
Wenlong Ji ◽  
Haowei He ◽  
Yaojie Chen
Keyword(s):  
Pitch Angle ◽  
Back Propagation ◽  
Water Jet ◽  
The State ◽  
Model Parameters ◽  
Propagation Time ◽  
Back Propagation Algorithm ◽  
Angle Error ◽  
Landing Point ◽  
Propagation Algorithm

In this paper, an intelligent water shooting robot system for situations of carrier shake and target movement is designed, which uses a 2 DOF (degree of freedom) robot as an actuator, a photoelectric camera to detect and track the desired target, and a gyroscope to keep the robot’s body stable when it is mounted on the motion carriers. Particularly, for the accurate shooting of the designed system, an online tuning model of the water jet landing point based on the back-propagation algorithm was proposed. The model has two stages. In the first stage, the polyfit function of Matlab is used to fit a model that satisfies the law of jet motion in ideal conditions without interference. In the second stage, the model uses the back-propagation algorithm to update the parameters online according to the visual feedback of the landing point position. The model established by this method can dynamically eliminate the interference of external factors and realize precise on-target shooting. The simulation results show that the model can dynamically adjust the parameters according to the state relationship between the landing point and the desired target, which keeps the predicted pitch angle error within 0.1°. In the test on the actual platform, when the landing point is 0.5 m away from the position of the desired target, the model only needs 0.3 s to adjust the water jet to hit the target. Compared to the state-of-the-art method, GA-BP (genetic algorithm-back-propagation), the proposed method’s predicted pitch angle error is within 0.1 degree with 1/4 model parameters, while costing 1/7 forward propagation time and 1/200 back-propagation calculation time.

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