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Decision support systems are essential for maintaining grid stability in low-carbon power systems, such as wind power plants, by providing real-time alerts to control room operators regarding potential events, including Wind Power Ramp…

This paper presents an innovative deep learning pipeline which estimates the relative pose of a spacecraft by incorporating the temporal information from a rendezvous sequence. It leverages the performance of long short-term memory (LSTM)…

Coronal mass ejections (CMEs) are large-scale expulsions of plasma and magnetic flux from the Sun's corona into the heliosphere. In interplanetary space they are referred to as interplanetary CMEs (ICMEs), often characterised by a shock, a…

Understanding the magnetic configuration of the source regions of coronal mass ejections (CMEs) is vital in order to determine the trigger and driver of these events. Observations of four CME productive active regions are presented here,…

Physical Flow Networks are different infrastructure networks that allow the flow of physical commodities through edges between its constituent nodes. These include power grid, natural gas transmission network, water pipelines etc. In such…

Deep learning has drawn a lot of interest in recent years due to its effectiveness in processing big and complex observational data gathered from diverse instruments. Here we propose a new deep learning method, called SolarUnet, to identify…

We present a new model of magnetic reconnection in the presence of turbulence, applicable when the magnetic helicity is non-zero. The new model differs from the Lazarian-Vishniac turbulent reconnection theory by emphasizing the role of…

Magnetic reconnection plays an important role in converting energy while modifying field topology. This process takes place in varied plasma environments in which the transport of magnetic flux is intrinsic. Identifying active magnetic…

Three-dimensional magnetic topology is crucial to understanding the explosive release of magnetic energy in the corona during solar flares. Much attention has been given to the pre-flare magnetic topology to identify candidate sites of…

Coronal mass ejections (CMEs) are powerful drivers of space weather, with magnetic flux ropes (MFRs) widely regarded as their primary precursors. However, the variation in reconnection flux during the evolution of MFR during CME eruptions…

Magnetic clouds (MCs) are large-scale interplanetary transient structures in the heliosphere that travel from the Sun into the interplanetary medium. The internal magnetic field lines inside the MCs are twisted, forming a flux rope (FR).…

We present multi-point in situ observations of a complex sequence of coronal mass ejections (CMEs) which may serve as a benchmark event for numerical and empirical space weather prediction models. On 2010 August 1, instruments on various…

The combination of magnetohydrodynamic (MHD) simulation and multi-wavelength observations is an effective way to study mechanisms of magnetic flux rope eruption. We develop a data-driven MHD model using the zero-$\beta$ approximation. The…

We compare the magnetic helicity in the 17-18 March 2013 interplanetary coronal mass ejection (ICME) flux-rope at 1 AU and in its solar counterpart. The progenitor coronal mass ejection (CME) erupted on 15 March 2013 from NOAA active region…

In recent years, the robotics community has extensively examined methods concerning the place recognition task within the scope of simultaneous localization and mapping applications.This article proposes an appearance-based loop closure…

We present a novel deep learning framework for flow field predictions in irregular domains when the solution is a function of the geometry of either the domain or objects inside the domain. Grid vertices in a computational fluid dynamics…

Modeling the behavior of coupled networks is challenging due to their intricate dynamics. For example in neuroscience, it is of critical importance to understand the relationship between the functional neural processes and anatomical…

Solar wind measurements carried out by NASA's Wind spacecraft before, during and after the passing of an interplanetary coronal mass ejection (ICME) detected on 12-14 September 2014 have been used in order to examine several properties of…

In the complex domain of microfluidics systems, analysing fluid flow patterns through random-shaped circular microchannels is significantly challenging task. Conventional approach of solving such problems using computational fluid dynamics…

This paper presents a machine learning methodology to improve the predictions of traditional RANS turbulence models in channel flows subject to strong variations in their thermophysical properties. The developed formulation contains several…