Subscribe to the gold package and get unlimited access to Shamra Academy
Register a new userHow gas-dynamic flare models powered by Petschek reconnection differ from those with ad hoc energy sources
47
0
0.0
(
0
)
Ask ChatGPT about the research
No Arabic abstract
Aspects of solar flare dynamics, such as chromospheric evaporation and flare light-curves, have long been studied using one-dimensional models of plasma dynamics inside a static flare loop, subjected to some energy input. While extremely successful at explaining the observed characteristics of flares, all such models so far have specified energy input ad hoc, rather than deriving it self-consistently. There is broad consensus that flares are powered by magnetic energy released through reconnection. Recent work has generalized Petscheks basic reconnection scenario, topological change followed by field line retraction and shock heating, to permit its inclusion into a one-dimensional flare loop model. Here we compare the gas dynamics driven by retraction and shocking to those from more conventional static loop models energized by ad hoc source terms. We find significant differences during the first minute, when retraction leads to larger kinetic energies and produces higher densities at the loop top, while ad hoc heating tends to rarify the loop top. The loop-top density concentration is related to the slow magnetosonic shock, characteristic of Petscheks model, but persists beyond the retraction phase occurring in the outflow jet. This offers an explanation for observed loop-top sources of X-ray and EUV emission, with advantages over that provided by ad hoc heating scenarios. The cooling phases of the two models are, however, notably similar to one another, suggesting observations at that stage will yield little information on the nature of energy input.
rate research
Read More
White-light flares (WLFs), first observed in 1859, refer to a type of solar flares showing an obvious enhancement of the visible continuum emission. This type of enhancement often occurs in most energetic flares, and is usually interpreted as a consequence of efficient heating in the lower solar atmosphere through non-thermal electrons propagating downward from the energy release site in the corona. However, this coronal-reconnection model has difficulty in explaining the recently discovered small WLFs. Here we report a C2.3 white-light flare, which are associated with several observational phenomena: fast decrease in opposite-polarity photospheric magnetic fluxes, disappearance of two adjacent pores, significant heating of the lower chromosphere, negligible increase of hard X-ray flux, and an associated U-shaped magnetic field configuration. All these suggest that this white-light flare is powered by magnetic reconnection in the lower part of the solar atmosphere rather than by reconnection higher up in the corona.
This paper reports experimental results on self-organizing wireless networks carried by small flying robots. Flying ad hoc networks (FANETs) composed of small unmanned aerial vehicles (UAVs) are flexible, inexpensive and fast to deploy. This makes them a very attractive technology for many civilian and military applications. Due to the high mobility of the nodes, maintaining a communication link between the UAVs is a challenging task. The topology of these networks is more dynamic than that of typical mobile ad hoc networks (MANETs) and of typical vehicle ad hoc networks (VANETs). As a consequence, the existing routing protocols designed for MANETs partly fail in tracking network topology changes. In this work, we compare two different routing algorithms for ad hoc networks: optimized link-state routing (OLSR), and predictive-OLSR (P-OLSR). The latter is an OLSR extension that we designed for FANETs; it takes advantage of the GPS information available on board. To the best of our knowledge, P-OLSR is currently the only FANET-specific routing technique that has an available Linux implementation. We present results obtained by both Media Access Control (MAC) layer emulations and real-world experiments. In the experiments, we used a testbed composed of two autonomous fixed-wing UAVs and a node on the ground. Our experiments evaluate the link performance and the communication range, as well as the routing performance. Our emulation and experimental results show that P-OLSR significantly outperforms OLSR in routing in the presence of frequent network topology changes.
Cognitive ad-hoc networks allow users to access an unlicensed/shared spectrum without the need for any coordination via a central controller and are being envisioned for futuristic ultra-dense wireless networks. The ad-hoc nature of networks require each user to learn and regularly update various network parameters such as channel quality and the number of users, and use learned information to improve the spectrum utilization and minimize collisions. For such a learning and coordination task, we propose a distributed algorithm based on a multi-player multi-armed bandit approach and novel signaling scheme. The proposed algorithm does not need prior knowledge of network parameters (users, channels) and its ability to detect as well as adapt to the changes in the network parameters thereby making it suitable for static as well as dynamic networks. The theoretical analysis and extensive simulation results validate the superiority of the proposed algorithm over existing state-of-the-art algorithms.
In models of fast magnetic reconnection, flux transfer occurs within a small portion of a current sheet triggering stored magnetic energy to be thermalized by shocks. When the initial current sheet separates magnetic fields which are not perfectly anti-parallel, i.e. they are skewed, magnetic energy is first converted to bulk kinetic energy and then thermalized in slow magnetosonic shocks. We show that the latter resemble parallel shocks or hydrodynamic shocks for all skew angles except those very near the anti-parallel limit. As for parallel shocks, the structures of reconnection-driven slow shocks are best studied using two-fluid equations in which ions and electrons have independent temperature. Time-dependent solutions of these equations can be used to predict and understand the shocks from reconnection of skewed magnetic fields. The results differ from those found using a single-fluid model such as magnetohydrodynamics. In the two-fluid model electrons are heated indirectly and thus carry a heat flux always well below the free-streaming limit. The viscous stress of the ions is, however, typically near the fluid-treatable limit. We find that for a wide range of skew angles and small plasma beta an electron conduction front extends ahead of the slow shock but remains within the outflow jet. In such cases conduction will play a more limited role in driving chromospheric evaporation than has been predicted based on single-fluid, anti-parallel models.
Drones have been getting more and more popular in many economy sectors. Both scientific and industrial communities aim at making the impact of drones even more disruptive by empowering collaborative autonomous behaviors -- also known as swarming behaviors -- within fleets of multiple drones. In swarming-powered 3D mapping missions, unmanned aerial vehicles typically collect the aerial pictures of the target area whereas the 3D reconstruction process is performed in a centralized manner. However, such approaches do not leverage computational and storage resources from the swarm members.We address the optimization of a swarm-powered distributed 3D mapping mission for a real-life humanitarian emergency response application through the exploitation of a swarm-powered ad hoc cloud. Producing the relevant 3D maps in a timely manner, even when the cloud connectivity is not available, is crucial to increase the chances of success of the operation. In this work, we present a mathematical programming heuristic based on decomposition and a variable neighborhood search heuristic to minimize the completion time of the 3D reconstruction process necessary in such missions. Our computational results reveal that the proposed heuristics either quickly reach optimality or improve the best known solutions for almost all tested realistic instances comprising up to 1000 images and fifteen drones.
Log in to be able to interact and post comments
comments
Fetching comments
Sign in to be able to follow your search criteria
