Finite element modelling in integral design strategies of form- and bending-active hybrid structures

This paper discusses form-finding and simulation strategies for form- and bending-active hybrid structures, with practical feedback from two realised projects. Next to some general aspects of computational form-finding approaches with focus on finite element methods (FEM), the influence of changing mechanical properties of elastic beams on the resultant form-found hybrid system will be discussed on an umbrella structure with integrated bendingactive beam elements. Alongside the question of simulation strategies comes the search for a practical design setup to establish an FEM environment that is cross integrating information from various other modelling environments. This is discussed through the case study project M1 where physical form-finding and vector-based spring methods are utilised to generate input data for the FEM simulation

I.C.E.: a Transportable Atomic Inertial Sensor for Test in Microgravity

We present our the construction of an atom interferometer for inertial sensing in microgravity, as part of the I.C.E. (\textit{Interf\'{e}rom\'{e}trie Coh\'{e}rente pour l'Espace}) collaboration. On-board laser systems have been developed based on fibre-optic components, which are insensitive to mechanical vibrations and acoustic noise, have sub-MHz linewidth, and remain frequency stabilised for weeks at a time. A compact, transportable vacuum system has been built, and used for laser cooling and magneto-optical trapping. We will use a mixture of quantum degenerate gases, bosonic $^{87}$Rb and fermionic $^{40}$K, in order to find the optimal conditions for precision and sensitivity of inertial measurements. Microgravity will be realised in parabolic flights lasting up to 20s in an Airbus. We show that the factors limiting the sensitivity of a long-interrogation-time atomic inertial sensor are the phase noise in reference frequency generation for Raman-pulse atomic beam-splitters and acceleration fluctuations during free fall

NBSymple, a double parallel, symplectic N-body code running on Graphic Processing Units

We present and discuss the characteristics and performances, both in term of computational speed and precision, of a numerical code which numerically integrates the equation of motions of N 'particles' interacting via Newtonian gravitation and move in an external galactic smooth field. The force evaluation on every particle is done by mean of direct summation of the contribution of all the other system's particle, avoiding truncation error. The time integration is done with second-order and sixth-order symplectic schemes. The code, NBSymple, has been parallelized twice, by mean of the Computer Unified Device Architecture to make the all-pair force evaluation as fast as possible on high-performance Graphic Processing Units NVIDIA TESLA C 1060, while the O(N) computations are distributed on various CPUs by mean of OpenMP Application Program. The code works both in single precision floating point arithmetics or in double precision. The use of single precision allows the use at best of the GPU performances but, of course, limits the precision of simulation in some critical situations. We find a good compromise in using a software reconstruction of double precision for those variables that are most critical for the overall precision of the code. The code is available on the web site astrowww.phys.uniroma1.it/dolcetta/nbsymple.htmlComment: Paper composed by 29 pages, including 9 figures. Submitted to New Astronomy

Modelling of content-aware indicators for effective determination of shot boundaries in compressed MPEG videos

In this paper, a content-aware approach is proposed to design multiple test conditions for shot cut detection, which are organized into a multiple phase decision tree for abrupt cut detection and a finite state machine for dissolve detection. In comparison with existing approaches, our algorithm is characterized with two categories of content difference indicators and testing. While the first category indicates the content changes that are directly used for shot cut detection, the second category indicates the contexts under which the content change occurs. As a result, indications of frame differences are tested with context awareness to make the detection of shot cuts adaptive to both content and context changes. Evaluations announced by TRECVID 2007 indicate that our proposed algorithm achieved comparable performance to those using machine learning approaches, yet using a simpler feature set and straightforward design strategies. This has validated the effectiveness of modelling of content-aware indicators for decision making, which also provides a good alternative to conventional approaches in this topic

Analysis of 2D airglow imager data with respect to dynamics using machine learning

We demonstrate how machine learning can be easily applied to support the analysis of large quantities of excited hydroxyl (OH*) airglow imager data. We use a TCN (temporal convolutional network) classification algorithm to automatically pre-sort images into the three categories “dynamic” (images where small-scale motions like turbulence are likely to be found), “calm” (clear-sky images with weak airglow variations) and “cloudy” (cloudy images where no airglow analyses can be performed). The proposed approach is demonstrated using image data of FAIM 3 (Fast Airglow IMager), acquired at Oberpfaffenhofen, Germany, between 11 June 2019 and 25 February 2020, achieving a mean average precision of 0.82 in image classification. The attached video sequence demonstrates the classification abilities of the learned TCN. Within the dynamic category, we find a subset of 13 episodes of image series showing turbulence. As FAIM 3 exhibits a high spatial (23 m per pixel) and temporal (2.8 s per image) resolution, turbulence parameters can be derived to estimate the energy diffusion rate. Similarly to the results the authors found for another FAIM station (Sedlak et al., 2021), the values of the energy dissipation rate range from 0.03 to 3.18 W kg−1.</p

Detecting inertial effects with airborne matter-wave interferometry

Inertial sensors relying on atom interferometry offer a breakthrough advance in a variety of applications, such as inertial navigation, gravimetry or ground- and space-based tests of fundamental physics. These instruments require a quiet environment to reach their performance and using them outside the laboratory remains a challenge. Here we report the first operation of an airborne matter-wave accelerometer set up aboard a 0g plane and operating during the standard gravity (1g) and microgravity (0g) phases of the flight. At 1g, the sensor can detect inertial effects more than 300 times weaker than the typical acceleration fluctuations of the aircraft. We describe the improvement of the interferometer sensitivity in 0g, which reaches 2 x 10-4 ms-2 / \surdHz with our current setup. We finally discuss the extension of our method to airborne and spaceborne tests of the Universality of free fall with matter waves.Comment: 7 pages, 6 figures. The final version of this article is available in OPEN access (free) from the editor website at http://www.nature.com/ncomms/journal/v2/n9/full/ncomms1479.htm

Robust 3D face capture using example-based photometric stereo

We show that using example-based photometric stereo, it is possible to achieve realistic reconstructions of the human face. The method can handle non-Lambertian reflectance and attached shadows after a simple calibration step. We use spherical harmonics to model and de-noise the illumination functions from images of a reference object with known shape, and a fast grid technique to invert those functions and recover the surface normal for each point of the target object. The depth coordinate is obtained by weighted multi-scale integration of these normals, using an integration weight mask obtained automatically from the images themselves. We have applied these techniques to improve the PHOTOFACE system of Hansen et al. (2010). © 2013 Elsevier B.V. All rights reserved