On the distance of PG 1553+11. A lineless BL Lac object active in the TeV band

Context: The redshift of PG 1553+11, a bright BL Lac object (V~14), is still unknown. It has been recently observed in the TeV band, a fact that offers an upper limit for the redshift z<0.4. Aims: We intend to provide a lower limit for the distance of the object. Methods: We used a chi^2 procedure to constrain the apparent magnitude of the host galaxy in archived HST images. Supposing that the host galaxy is typical of BL Lac objects (M_{R} -22.8), a lower limit to the distance can be obtained from the limit on the apparent magnitude of the host galaxy. Results: Using the 3 sigma limit on the host galaxy magnitude, the redshift is found to be greater or equal to 0.25. Conlusions: The redshift of PG 1553+11 is probably in the range z=0.3-0.4, making this object the most distant extragalactic source so far detected in the TeV energies. We suggest that other bright BL Lac objects of unknown redshift and similar spectroscopic characteristics may be interesting targets for TeV observations.Comment: Accepted for publication in A&A letters, 4 pages, 5 figure

Spectroscopy of BL Lac objects of extraordinary luminosity

Aims. We aim to determine the redshift (or stringent lower limits) of a number of bright BL Lacs objects. Methods. We secured medium resolution optical and near-infrared spectra of 4 bright BL Lac objects of unknown redshift using the spectrograph X-Shooter at the ESO-VLT. Results. In spite of the high quality of the spectra and the extended spectral range of the observations we have not detected intrisic spectral features for these sources. However we are able to provide strigent lower limits to their redshift. In particular, for the two TeV sources PG 1553+113 and H 1722+119 we infer z > 0.30 and z > 0.35 respectively. We also detect an intervening Ca II absorption doublet in the spectrum of MH 2136-428 that is ascribed to the the halo of a nearby giant elliptical galaxy at \sim 100 kpc of projected distance. Conclusions. Under the hypothesis that all BL Lacs are hosted by luminous bulge dominated galaxies, the present state of art spectroscopic observations of bright BL Lacs indicate that these objects are likely sources with extremely beamed nuclear emission . We present simulations to show under which circustances it will be possible to probe this hypothesis from the detection of very weak absorptions using the next generation of extremely large optical telescopes.Comment: Accepted for publication in A&

Imaging Redshift Estimates for BL Lacertae Objects

We have obtained high dynamic range, good natural seeing i' images of BL Lacertae objects (BL Lacs) to search for the AGN host and thus constrain the source redshift. These objects are drawn from a sample of bright flat-spectrum radio sources that are either known (via recent Fermi LAT observations) gamma-ray emitters or similar sources that might be detected in continuing gamma-ray observations. All had spectroscopic confirmation as BL Lac sources, but no redshift solution. We detected hosts for 25/49 objects. As these galaxies have been argued to be standard candles, our measured host magnitudes provide redshift estimates (ranging from 0.2--1.0). Lower bounds are established on the redshifts of non-detections. The mean of the fit redshifts (and lower limits) is higher than those of spectroscopic solutions in the radio- and gamma-ray- loud parent samples, suggesting corrections may be needed for the luminosity function and evolution of these sources.Comment: 15 pages, to appear in the Astrophysical Journa

ESO VLT Optical Spectroscopy of BL Lac Objects IV. New spectra and properties of the full sample

We present the last chapter of a spectroscopy program aimed at deriving the redshift or a lower limit to the redshift of BL Lac objects using medium resolution spectroscopy. Here we report new spectra for 33 BL Lac object candidates obtained in 2008-2009 confirming the BL Lac nature of 25 sources and for 5 objects we obtained new redshifts. These new observations are combined with our previous data in order to construct a homogeneous sample of \sim 70 BL Lacs with high quality spectroscopy. All these spectra can be accessed at the website http://www.oapd.inaf.it/zbllac/. The average spectrum, beaming properties of the full sample, discussion on intervening systems and future perspectives are addressed.Comment: 25 pages, 13 Figures. Accepted for publication in the Astronomical Journa

Sensor network optimization for damage detection on aluminium stiffened helicopter panels

Health and Usage Monitoring Systems (HUMS) has received considerable attention from the helicopter community in recent years with the declared aim to increase flight safety, increase mission reliability, extend duration of life limited components and of course reduce the maintenance costs. The latter is about 25 per cent of the direct operating cost of the helicopter, thus playing an important role especially in the case of the ageing aircrafts. In particular, with respect to helicopter fuselages, only some attempts were carried out to monitor directly on-line the damage accumulation and propagation during life. In this field, and in particular in the military applications, an integrated and reliable system for monitoring the damage in the fuselage and for evaluating the time inspections and remaining life (prognosis) is missing. However, because of the presence of many vibratory loads, the diagnosis of helicopter structures is very critical. From one hand, a very large number of sensors would be needed for a robust appreciation of the structural health, from the other hand the industrialization of the product brings the need for a low impact over the existing structures, or toward a reduction in the allowed amount of sensors. As a result, comes the importance for an optimization of the sensor network, with the aim to find out the regions inside the structure which are the most sensible to a damage and at the same time robust to noise. The aim of the present work is to define a methodology for optimising the sensors position inside an helicopter fuselage panel in order to obtain the best compromise between the simplicity and the robustness of a sensor network. In particular, a Finite Element (FE) model will be used to create a database of various damages inside the structure, thus consequently optimising the network sensitivity to any damage. The evaluation of the network performances is provided when some realistic noise [1,2] is added to the FE calculation

A Fuzzy-set-based Joint Distribution Adaptation Method for Regression and its Application to Online Damage Quantification for Structural Digital Twin

Online damage quantification suffers from insufficient labeled data. In this context, adopting the domain adaptation on historical labeled data from similar structures/damages to assist the current diagnosis task would be beneficial. However, most domain adaptation methods are designed for classification and cannot efficiently address damage quantification, a regression problem with continuous real-valued labels. This study first proposes a novel domain adaptation method, the Online Fuzzy-set-based Joint Distribution Adaptation for Regression, to address this challenge. By converting the continuous real-valued labels to fuzzy class labels via fuzzy sets, the conditional distribution discrepancy is measured, and domain adaptation can simultaneously consider the marginal and conditional distribution for the regression task. Furthermore, a framework of online damage quantification integrated with the proposed domain adaptation method is presented. The method has been verified with an example of a damaged helicopter panel, in which domain adaptations are conducted across different damage locations and from simulation to experiment, proving the accuracy of damage quantification can be improved significantly even in a noisy environment. It is expected that the proposed approach to be applied to the fleet-level digital twin considering the individual differences.Comment: 29 pages, 10 figure

A method for determining the distribution of carbon nanotubes in nanocomposites by electric conductivity

Carbon nanotube (CNT) polymer nanocomposites are one of the most promising materials due to their remarkable mechanical properties as well as the electrical conductivity, which offers the capability of monitoring the deformation and damage of composite structures by measuring the related conductivity variations. However, quantifying the distribution of CNTs inside the material remains a challenge with respects to both experimental and numerical works. In the current study, the electrical conductivity was used to determine the microstructure of CNT-reinforced polymer. By introducing a modified parameter related to the polar angle of CNTs, the mechanical properties as well as the electrical conductivity change with respect to deformation of nanocomposites can be replicated. After validation by experimental data from the multi-walled CNT/polymer nanocompo sites under tensile loading, the capability of the current method was then studied for composites with various weight fractions of nanotubes. (C) 2022 The Authors. Published by Elsevier B.V

Particle filter-based damage prognosis using online feature fusion and selection

Damage prognosis generally resorts to damage quantification functions and evolution models to quantify the current damage state and to predict the future states and the remaining useful life (RUL). The former typically consists of a function describing the relationship between the damage state and a statistical feature extracted from the measured signals, thus the prognostic performance will strongly depend on the selection of a proper feature. Given the best feature may vary for different specimens or even at each time instant for the same specimen during damage progression, such selection is a challenging task but has received little investigation so far. In this context, this paper proposes a particle filter-based damage prognosis framework, which involves an online feature fusion and selection scheme. A prognostic model is considered for each feature, with a multivariate process equation, formulated using both a damage degradation function and a bias parameter, and a measurement equation linking the damage state and that feature considering a data-driven model and the bias. One PF is used to estimate the damage state, its evolution parameters, and the bias for each model. Then, at each step, the feature with the smallest estimated bias is selected as the best feature providing the most likely state vectors and is used to select the most likely samples of the damage state and growth parameters for predicting the RUL and for calculating the prior at the next step. The proposed prognostic framework is demonstrated by an experimental study, where an aluminum lug structure subject to fatigue crack growth is monitored by a Lamb wave measurement system