The interstellar medium is characterized by an intricate filamentary network that exhibits complex structures. These show a variety of different shapes (e.g. junctions, rings, etc.) deviating strongly from the usually assumed cylindrical shape. A possible formation mechanism are filament mergers that we analyse in this study. Indeed, the proximity of filaments in networks suggests mergers to be rather likely. As the merger has to be faster than the end dominated collapse of the filament along its major axis, we expect three possible results: (a) The filaments collapse before a merger can happen, (b) the merged filamentary complex shows already signs of cores at the edges, or (c) the filaments merge into a structure which is not end-dominated. We develop an analytic formula for the merging and core-formation time-scale at the edge and validate our model via hydrodynamical simulations with the adaptive-mesh-refinement-code ramses. This allows us to predict the outcome of a filament merger, given different initial conditions which are the initial distance and the respective line-masses of each filament as well as their relative velocities.

Simulations of idealized star-forming filaments of finite length typically show core growth that is dominated by two cores forming at its respective end. The end cores form due to a strong increasing acceleration at the filament ends that leads to a sweep-up of material during the filament collapse along its axis. As this growth mode is typically faster than any other core formation mode in a filament, the end cores usually dominate in mass and density compared to other cores forming inside a filament. However, observations of star-forming filaments do not show this prevalence of cores at the filament ends. We explore a possible mechanism to slow the growth of the end cores using numerical simulations of simultaneous filament and embedded core formation, in our case a radially accreting filament forming in a finite converging flow. While such a set-up still leads to end cores, they soon begin to move inwards and a density gradient is formed outside of the cores by the continued accumulation of material. As a result, the outermost cores are no longer located at the exact ends of the filament and the density gradient softens the inward gravitational acceleration of the cores. Therefore, the two end cores do not grow as fast as expected and thus do not dominate over other core formation modes in the filament.

Using numerical simulations, we investigate the gravitational evolution of filamentary molecular cloud structures and their condensation into dense protostellar cores. One possible process is the so-called edge effect, the pile-up of matter at the end of the filament due to self-gravity. This effect is predicted by theory but only rarely observed. To get a better understanding of the underlying processes we used a simple analytic approach to describe the collapse and the corresponding collapse time. We identify a model of two distinct phases. The first phase is free fall dominated, due to the self-gravity of the filament. In the second phase, after the turning point, the collapse is balanced by the ram pressure, produced by the inside material of the filament, which leads to a constant collapse velocity. This approach reproduces the established collapse time of uniform density filaments and agrees well with our hydrodynamic simulations. In addition, we investigate the influence of different radial density profiles on the collapse. We find that the deviations compared to the uniform filament are less than 10 per cent. Therefore, the analytic collapse model of the uniform density filament is an excellent general approach.

A continuous increase in artificial intelligence (AI)-based functions can be expected for future aviation systems, posing significant challenges to traditional development processes. Established systems engineering frameworks, such as the V-model, are not adequately addressing the novel challenges associated with AI-based systems. Consequently, the European Union Aviation Safety Agency (EASA) introduced the W-shaped process, an advancement of the V-model, to set a regulatory framework for the novel challenges of AI Engineering. In contrast, the agile Development Operations (DevOps) approach, widely adopted in software development, promotes a never-ending iterative development process. This article proposes a novel concept that integrates aspects of DevOps into the W-shaped process to create an AI Engineering framework suitable for aviation-specific applications. Furthermore, it builds upon proven ideas and methods using AI Engineering efforts from other domains. The proposed extension of the W-shaped process, compatible with ongoing standardizations from the G34/WG-114 Standardization Working Group, a joint effort between EUROCAE and SAE, addresses the need for a rigorous development process for AI-based systems while acknowledging its limitations and potential for future advancements. The proposed framework allows for a re-evaluation of the AI/ML constituent based on operational information, enabling improvements of the system’s capabilities with each iteration.

The onset of star formation is set by the collapse of filaments in the interstellar medium. From a theoretical point of view, an isolated cylindrical filament forms cores via the edge effect. Due to the self-gravity of a filament, the strong increase in acceleration at both ends leads to a pile-up of matter which collapses into cores. However, this effect is rarely observed. Most theoretical models consider a sharp density cut-off at the edge of the filament, whereas a smoother transition is more realistic and would also decrease the acceleration at the ends of the filament. We show that the edge effect can be significantly slowed down by a density gradient, although not completely avoided. However, this allows perturbations inside the filament to grow faster than the edge. We determine the critical density gradient for which the time-scales are equal and find it to be of the order of several times the filament radius. Hence, the density gradient at the ends of a filament is an essential parameter for fragmentation and the low rate of observed cases of the edge effect could be naturally explained by shallow gradients.

We suggest that filaments in star-forming regions undergo frequent mergers. As stellar nurseries, filaments play a vital role in understanding star formation and mergers could pave the way for understanding the formation of more complex filamentary systems, such as networks and hubs. We compare the physical properties derived from hydrodynamic ramses simulations of merging filaments to those obtained from ALMA observations towards the LDN 1641-North region in Orion. We find similarities in the distributions of line-mass, column density, and velocity dispersion. Such common features support the hypothesis of filament mergers shaping the structure of the interstellar medium.