A multiphysics and multiscale software environment for modeling astrophysical systems

We present MUSE, a software framework for combining existing computational tools for different astrophysical domains into a single multiphysics, multiscale application. MUSE facilitates the coupling of existing codes written in different languages by providing inter-language tools and by specifying an interface between each module and the framework that represents a balance between generality and computational efficiency. This approach allows scientists to use combinations of codes to solve highly coupled problems without the need to write new codes for other domains or significantly alter their existing codes. MUSE currently incorporates the domains of stellar dynamics, stellar evolution and stellar hydrodynamics for studying generalized stellar systems. We have now reached a “Noah’s Ark” milestone, with (at least) two available numerical solvers for each domain. MUSE can treat multiscale and multiphysics systems in which the time- and size-scales are well separated, like simulating the evolution of planetary systems, small stellar associations, dense stellar clusters, galaxies and galactic nuclei. In this paper we describe three examples calculated using MUSE: the merger of two galaxies, the merger of two evolving stars, and a hybrid N-body simulation. In addition, we demonstrate an implementation of MUSE on a distributed computer which may also include special-purpose hardware, such as GRAPEs or GPUs, to accelerate computations. The current MUSE code base is publicly available as open source at http://muse.li.     

Comparison of ladderane phospholipid and core lipids as indicators for anaerobic ammonium oxidation (anammox) in marine sediments

We investigated anaerobic ammonium oxidation (anammox) in continental shelf and slope sediments of the Irish and Celtic Seas by using anammox specific ladderane biomarker lipids. We used the presence of an intact ladderane phospholipid as a direct indicator for living anammox bacteria, and compared it with the abundance of ladderane core lipids derived from both living and dead bacterial biomass. All investigated sediments contained ladderane core lipids as well as the intact ladderane phospholipid, in agreement with ¹⁵N-labeling experiments, which revealed anammox activity at all sites. Ladderane core lipid and intact ladderane phospholipid concentrations were significantly correlated (R² = 0.957 and 0.464, respectively) with anammox activity over the transect of the continental shelf and slope sediments. In the Irish Sea (50-100 m water depth) highest abundances of the intact ladderane phospholipid were found in the upper 2 cm of the sediment, indicating a zone of active anammox. A sharp decline further down-core suggested a strong decrease in anammox biomass and rapid degradation of the intact lipids. In comparison, ladderane core lipids were 1-2 orders of magnitude higher in concentration than the intact ladderane phospholipid and accumulated as dead cell remnants with depth. In the slope sediments of the Celtic Sea both ladderane core lipids and the intact ladderane phospholipid were found in sediments at water depths ranging from 500 to 2000 m. Here, anammox seemed to be active at greater depths of the sediment (>2 cm). Mean abundances of both intact and core ladderane lipids in whole sediment cores increased downslope, indicating an increasing importance of anammox in deeper slope sediments.     

Application of wavelet transform analysis to landslide generated waves

The aim of this paper is to illustrate the results of a preliminary study on aerial landslide-generated waves, which has been mainly intended to establish a method for analyzing water surface records. Some simple physical experiments, reproducing the Scott Russell's wave generator, were carried out in a small two-dimensional wave flume; the Wavelet Transform (WT) is applied to analyze wave measurements and it is shown that useful information can be obtained by means of this technique. The celerity of impulsively generated waves, reflection by an overflow structure and seiching phenomena of the flume are studied. A discussion of the results along with some remarks about ongoing research is also given.     

Sediment transport at the network scale and its link to channel morphology in the braided Vjosa River system

In this article we apply the CASCADE network-scale sediment connectivity model to the Vjosa River in Albania. The Vjosa is one of the last unimpaired braided rivers in Europe and, at the same time, a data scarce environment, which limits our ability to model how this pristine river might respond to future human disturbance. To initialize the model, we use remotely sensed data and modeled hydrology from a regional model. We perform a reach-by-reach optimization of surface grain size distribution (GSD) and bedload transport capacity to ensure equilibrium conditions throughout the network. In order to account for the various sources of uncertainty in the calculation of transport capacity, we performed a global sensitivity analysis. The modeled GSD distributions generated by the sensitivity analysis generally match the six GSDs measured at different locations within the network. The modeled bedload sediment fluxes increase systematically downstream, and annual fluxes at the outlet of the Vjosa are well within an order of magnitude of fluxes derived from previous estimates of the annual suspended sediment load. We then use the modeled sediment fluxes as input to a set of theoretically derived functions that successfully discriminate between multi-thread and single-thread channel patterns. This finding provides additional validation of the model results by showing a clear connection between modeled sediment concentrations and observed river morphology. Finally, we observe that a reduction in sediment flux of about 50% (e.g., due to dams) would likely cause existing braided reaches to shift toward single thread morphology. The proposed method is widely applicable and opens a new avenue for application of network-scale sediment models that aid in the exploration of river stability to changes in water and sediment fluxes.     

A Minimal Spanning Tree algorithm for source detection in γ-ray images

We developed a source detection algorithm based on the Minimal Spanning Tree (MST), that is a graph-theoretical method useful for finding clusters in a given set of points. This algorithm is applied to γ-ray bi-dimensional images where the points correspond to the arrival direction of photons, and the possible sources are associated with the regions where they clusterize. Some filters to select these clusters and to reduce the spurious detections are introduced. An empirical study of the statistical properties of MST on random fields is carried out in order to derive some criteria to estimate the best filter values. We also introduce two parameters useful to verify the goodness of candidate sources. To show how the MST algorithm works in practice, we present an application to an EGRET observation of the Virgo field, at high Galactic latitude and with a low and rather uniform background, in which several sources are detected.     

Short-Period Fluctuations in Coronal Mass Ejection Activity during Solar Cycle 23

We have constructed a time series of the number of coronal mass ejections (CMEs) observed by SOHO/LASCO during solar cycle 23. Using spectral analysis techniques (the maximum entropy method and wavelet analysis) we found short-period (< one year) semiperiodic activity. Among others, we found interesting periodicities at 193, 36, 28, and 25 days. We discuss the implications of such short-period activity in terms of the emergence and escape of magnetic flux from the convection zone, through the low solar atmosphere (where these periodicities have been found for numerous activity parameters), toward interplanetary space. This analysis shows that CMEs remove the magnetic flux in a quasiperiodic process in a way similar to that of magnetic flux emergence and other solar eruptive activity.     

Orbital and mission planning constraints for the deflection of NEOs impacting on Earth

This paper is the third in a series. Paper 1 presented the results of numerical modeling of deflections of NEOs in route of collision with the Earth. The model was applied to a variety of dynamical cases including both asteroidal and cometary NEOs. Paper 2 introduced the concept of “distributed deflection,” i.e., the possibility to provide the ΔV necessary to deflect an object with a succession of maneuvers each of which would have been insufficient per se to obtain the desired result. In both papers no assumptions were made on the physical composition and structure of the NEO, nor on the details of the possible deflection maneuvers from the point of view of mission analysis. Moreover, ΔV-plots were computed assuming only along-track impulses (both in the positive and negative directions), because it is easy to demonstrate that in general this is energetically the most favorable configuration. Also in the present paper no assumptions were made on the physical composition and structure of the NEO, even if order of magnitude considerations are made on the physical feasibility of a deflection, in terms of the internal strength of the NEO. We present here the results of an investigation on the mission requirements necessary to deflect an object (or contribute to a succession of deflecting maneuvers) in terms of accessibility of the spacecraft terminal orbit from Earth with the current launchers.     

MARC: a robust method for multiple-aspect trajectory classification via space,time, and semantic embeddings

ABSTRACT

The increasing popularity of Location-Based Social Networks (LBSNs) and the semantic enrichment of mobility data in several contexts in the last years has led to the generation of large volumes of trajectory data. In contrast to GPS-based trajectories, LBSN and context-aware trajectories are more complex data, having several semantic textual dimensions besides space and time, which may reveal interesting mobility patterns. For instance, people may visit different places or perform different activities depending on the weather conditions. These new semantically rich data, known as multiple-aspect trajectories, pose new challenges in trajectory classification, which is the problem that we address in this paper. Existing methods for trajectory classification cannot deal with the complexity of heterogeneous data dimensions or the sequential aspect that characterizes movement. In this paper we propose MARC, an approach based on attribute embedding and Recurrent Neural Networks (RNNs) for classifying multiple-aspect trajectories, that tackles all trajectory properties: space, time, semantics, and sequence. We highlight that MARC exhibits good performance especially when trajectories are described by several textual/categorical attributes. Experiments performed over four publicly available datasets considering the Trajectory-User Linking (TUL) problem show that MARC outperformed all competitors, with respect to accuracy, precision, recall, and F1-score.     

The difficult challenge of modelling the non-linear elastic behaviour of soils within a theoretically sound framework

Hypo-elastic relations are often adopted to simulate the recoverable non-linear behaviour of soils within elasto-plastic constitutive models. In reality, they are unable to reproduce the elastic, ie, recoverable, response of materials; hence, they introduce severe inconsistencies in models based on the decomposition of the total strain tensor into its recoverable and permanent parts. Hyper-elasticity should then be used. However, existing models developed within this framework do not satisfy a number of fundamental theoretical requirements. A new hyper-elastic model is proposed, which is rigourously formulated by integrating some of the main relations which emerge from experimental results. The model satisfies all theoretical requirements and also possesses features that are fundamental for its numerical integration. The model can be considered as the correct hyper-elastic version of the classical hypo-elastic constitutive relation adopted in models based on the Critical State framework, such as the Modified Cam-Clay, with a constant Poisson's ratio.