Magnetohydrodynamic shocks in and above post-flare loops: two-dimensional simulation and a simplified model

Solar flares are an explosive phenomenon, where super-sonic flows and shocks are expected in and above the post-flare loops. To understand the dynamics of post-flare loops, a two-dimensional magnetohydrodynamic (2D MHD) simulation of a solar flare has been carried out. We found new shock structures in and above the post-flare loops, which were not resolved in the previous work by Yokoyama and Shibata 2001. To study the dynamics of flows along the reconnected magnetic field, kinematics and energetics of the plasma are investigated along selected field lines. It is found that shocks are crucial to determine the thermal and flow structures in the post-flare loops. On the basis of the 2D MHD simulation, we have developed a new post-flare loop model which we call the pseudo-2D MHD model. The model is based on the 1D MHD equations, where all the variables depend on one space dimension and all the three components of the magnetic and velocity fields are considered. Our pseudo-2D model includes many features of the multi-dimensional MHD processes related to magnetic reconnection (particularly MHD shocks), which the previous 1D hydrodynamic models are not able to include. We compare the shock formation and energetics of a specific field line in the 2D calculation with those in our pseudo-2D MHD model, and we found that they give similar results. This model will allow us to study the evolution of the post-flare loops in a wide parameter space without expensive computational cost and without neglecting important physics associated with magnetic reconnection.Comment: 51 pages, 22 figures. Accepted by Ap

Outfit Completion via Conditional Set Transformation

In this paper, we formulate the outfit completion problem as a set retrieval task and propose a novel framework for solving this problem. The proposal includes a conditional set transformation architecture with deep neural networks and a compatibility-based regularization method. The proposed method utilizes a map with permutation-invariant for the input set and permutation-equivariant for the condition set. This allows retrieving a set that is compatible with the input set while reflecting the properties of the condition set. In addition, since this structure outputs the element of the output set in a single inference, it can achieve a scalable inference speed with respect to the cardinality of the output set. Experimental results on real data reveal that the proposed method outperforms existing approaches in terms of accuracy of the outfit completion task, condition satisfaction, and compatibility of completion results.Comment: 8 pages, 8 figure

Broadband coherent Raman scattering spectroscopy at 50,000,000 spectra/s

Raman scattering spectroscopy is widely used as an analytical technique in various fields, but its measurement process tends to be slow due to the low scattering cross-section. In the last decade, various broadband coherent Raman scattering spectroscopy techniques have been developed to address this limitation, achieving a measurement rate of about 100 kSpectra/s. Here, we present a significantly increased measurement rate of 50 MSpectra/s, which is 500 times higher than the previous state-of-the-art, by developing time-stretch coherent Raman scattering spectroscopy. Our newly-developed system, based on a mode-locked Yb fiber laser, enables highly-efficient broadband excitation of molecular vibrations via impulsive stimulated Raman scattering with an ultrashort femtosecond pulse and sensitive time-stretch detection with a picosecond probe pulse at a high repetition rate of the laser. As a proof-of-concept demonstration, we measure broadband coherent Stokes Raman scattering spectra of organic compounds covering the molecular fingerprint region from 200 to 1,200 cm-1. This high-speed broadband vibrational spectroscopy technique holds promise for unprecedented measurements of sub-microsecond dynamics of irreversible phenomena and extremely high-throughput measurements

Multiple-hypothesis vision-based landing autonomy

Unmanned aerial vehicles (UAVs) need humans in the mission loop for many tasks, and landing is one of the tasks that typically involves a human pilot. This is because of the complexity of a maneuver itself and flight-critical factors such as recognition of a landing zone, collision avoidance, assessment of landing sites, and decision to abort the maneuver. Another critical aspect to be considered is the reliance of UAVs on GPS (global positioning system). A GPS system is not a reliable solution for landing in some scenarios (e.g. delivering a package in an urban city, and a surveillance UAV repatriating a home ship with the jammed signals), and a landing solely based on a GPS extremely decreases the UAV operation envelope. Vision is promising to achieve fully autonomous landing because it is a rich-sensing, light, affordable device that functions without any external resource. Although vision is a powerful tool for autonomous landing, the use of vision for state estimation requires extensive consideration. Firstly, vision-based landing faces a problem of occlusion. The target detected at a high altitude would be lost at certain altitudes while a vehicle descends; however, a small visual target can not be recognized at high altitude. Second, standard filtering methods such as extended Kalman filter (EKF) face difficulty due to the complex dynamics of the measurement error created due to the discrete pixel space, conversion from the pixel to physical units, the complex camera model, and complexity of detection algorithms. The vision sensor produces an unfixed number of measurements with each image, and the measurements may include false positives. Plus, the estimation system is excessively tasked in realistic conditions. The landing site would be moving, tilted, or close to an obstacle. The available landing location may not be limited to one. In addition to assessing these statuses, understanding the confidence of the estimations is also the tasks of the vision, and the decisions to initiate, continue, and abort the mission are made based on the estimated states and confidence. The system that handles those issues and consistently produces the navigation solution while a vehicle lands eliminates one of the limitations of the autonomous UAV operation. This thesis presents a novel state estimation system for UAV landing. In this system, vision data is used to both estimate the state of the vehicle and map the state of the landing target (position, velocity, and attitude) within the framework of simultaneous localization and mapping (SLAM). Using the SLAM framework, the system becomes resilient to a loss of GPS and other sensor failures. A novel vision algorithm that detects a portion of the marker is developed, and the stochastic properties of the algorithm are studied. This algorithm extends the detectable range of the vision system for any known marker. However, this vision algorithm produces highly nonlinear, non-Gaussian, and multi-modal error distribution, and a naive implementation of filters would not accurately estimate the states. A vision-aided navigation algorithm is derived within extended Kalman particle filter (PF-EKF) and Rao-Blackwellized particle filter (RBPF) frameworks in addition to a standard EKF framework. These multi-hypothesis approaches not only deal well with a highly nonlinear and non-Gaussian distribution of the measurement errors of vision but also result in numerically stable filters. The computational costs are reduced compared to a naive implementation of particle filter, and these algorithms run in real time. This system is validated through numerical simulation, image-in-the-loop simulation, and flight tests.Ph.D

Fingering behavior of flame spread over solid combustibles

In this study, the fingering pattern formation and the following flamelet spreading over three different kinds of thick combustibles, i.e., Poly methacrylate (PMMA), Poly ethylene (PE) and Poly carbonate (PC) were observed and the effective Lewis number correlation was validated. Experiments were performed with a narrow channel apparatus. In addition to the kinds of solid fuel materials, the channel height and the oxidizer velocity were varied as experimental parameters. An image analysis method was developed to quantify the number, diameter and spread rate of the flamelets. Replacing the fuel thickness into the thermal thickness, the effective Lewis number which is proposed for the smoldering combustion of thin fuel is remedied to include heat transfer perpendicular to the fuel surface. The result validates that the appearance condition of the fingering instability for thick combustibles is determined by the effective Lewis number. Hence, it is concluded that the observed phenomenon is inherently similar to that of smoldering. Further, it is shown that the non-dimensional flame diameter becomes nearly constant when the fingering instability occurs. It is believed that the correlation is useful when one wants to reproduce this phenomenon in a larger scale experiment