Asteroid models reconstructed from ATLAS photometry

Context. The Asteroid Terrestrial-impact Last Alert System (ATLAS) is an all-sky survey primarily aimed at detecting potentially hazardous near-Earth asteroids. Apart from the astrometry of asteroids, it also produces their photometric measurements that contain information about asteroid rotation and their shape. Aims. To increase the current number of asteroids with a known shape and spin state, we reconstructed asteroid models from ATLAS photometry that was available for approximately 180 000 asteroids observed between 2015 and 2018. Methods. We made use of the light-curve inversion method implemented in the Asteroids@home project to process ATLAS photometry for roughly 100 000 asteroids with more than a hundred individual brightness measurements. By scanning the period and pole parameter space, we selected those best-fit models that were, according to our setup, a unique solution for the inverse problem. Results. We derived ~2750 unique models, 950 of them were already reconstructed from other data and published. The remaining 1800 models are new. About half of them are only partial models, with an unconstrained pole ecliptic longitude. Together with the shape and spin, we also determined for each modeled asteroid its color index from the cyan and orange filter used by the ATLAS survey. We also show the correlations between the color index, albedo, and slope of the phase-angle function. Conclusions. The current analysis is the first inversion of ATLAS asteroid photometry, and it is the first step in exploiting the huge scientific potential that ATLAS photometry has. ATLAS continues to observe, and in the future, this data, together with other independent photometric measurements, can be inverted to produce more refined asteroid models.

Reconstruction of asteroid spin states from Gaia DR2 photometry

Context. In addition to stellar data, Gaia Data Release 2 (DR2) also contains accurate astrometry and photometry of about 14 000 asteroids covering 22 months of observations. Aims. We used Gaia asteroid photometry to reconstruct rotation periods, spin axis directions, and the coarse shapes of a subset of asteroids with enough observations. One of our aims was to test the reliability of the models with respect to the number of data points and to check the consistency of these models with independent data. Another aim was to produce new asteroid models to enlarge the sample of asteroids with known spin and shape. Methods. We used the lightcurve inversion method to scan the period and pole parameter space to create final shape models that best reproduce the observed data. To search for the sidereal rotation period, we also used a simpler model of a geometrically scattering triaxial ellipsoid. Results. By processing about 5400 asteroids with at least 10 observations in DR2, we derived models for 173 asteroids, 129 of which are new. Models of the remaining asteroids were already known from the inversion of independent data, and we used them for verification and error estimation. We also compared the formally best rotation periods based on Gaia data with those derived from dense lightcurves. Conclusions. We show that a correct rotation period can be determined even when the number of observations N is less than 20, but the rate of false solutions is high. For N > 30, the solution of the inverse problem is often successful and the parameters are likely to be correct in most cases. These results are very promising because the final Gaia catalogue should contain photometry for hundreds of thousands of asteroids, typically with several tens of data points per object, which should be sufficient for reliable spin reconstruction.

Biobjective Optimization of Vibration Performance of Steel-Spring Floating Slab Tracks by Four-Pole Parameter Method Coupled with Ant Colony Optimization

Steel-spring floating slab tracks are one of the most effective methods to reduce vibrations from underground railways, which has drawn more and more attention in scientific communities. In this paper, the steel-spring floating slab track located inTrack Vibration Abatement and Control Laboratorywas modeled with four-pole parameter method. The influences of the fastener damping ratio, the fastener stiffness, the steel-spring damping ratio, and the steel-spring stiffness were researched for the rail displacement and the foundation acceleration. Results show that the rail displacement and the foundation acceleration will decrease with the increase of the fastener stiffness or the steel-spring damping ratio. However, the rail displacement and the foundation acceleration have the opposite variation tendency for the fastener damping ratio and the steel-spring stiffness. In order to optimize the rail displacement and the foundation acceleration affected by the fastener damping ratio and the steel-spring stiffness at the same time, a multiobjective ant colony optimization (ACO) was employed. Eventually, Pareto optimal frontier of the rail displacement and the foundation acceleration was derived. Furthermore, the desirable values of the fastener damping ratio and the steel-spring stiffness can be obtained according to the corresponding Pareto optimal solution set.

Long-Term Prediction of Biological Wastewater Treatment Process Behavior via Wiener-Laguerre Network Model

A Wiener-Laguerre model with artificial neural network (ANN) as its nonlinear static part was employed to describe the dynamic behavior of a sequencing batch reactor (SBR) used for the treatment of dye-containing wastewater. The model was developed based on the experimental data obtained from the treatment of an effluent containing a reactive textile azo dye, Cibacron yellow FN-2R, bySphingomonas paucimobilisbacterium. The influent COD, MLVSS, and reaction time were selected as the process inputs and the effluent COD and BOD as the process outputs. The best possible result for the discrete pole parameter wasα=0.44. In order to adjust the parameters of ANN, the Levenberg-Marquardt (LM) algorithm was employed. The results predicted by the model were compared to the experimental data and showed a high correlation withR2>0.99and a low mean absolute error (MAE). The results from this study reveal that the developed model is accurate and efficacious in predicting COD and BOD parameters of the dye-containing wastewater treated by SBR. The proposed modeling approach can be applied to other industrial wastewater treatment systems to predict effluent characteristics.

A Method for Characterizing Elastic Structures in the Mid-Frequency Region

This work presents a method for characterizing elastic structures when spatially varying properties over the input and output contact regions are considered. Most analytical or experimental approaches, such as the four-pole parameter method, are limited by the inherent use of lumped quantities to represent critical parameters. When the excitation frequency increases, however, the structural wavelength becomes comparable to the dimensions of the contact region. As a result, the point-quantity assumption is no longer valid. To address this limitation, the work described here reformulates the traditional four-pole method in terms of quantities defined over planes. Consequently, spatial variations across the region connecting the structures can be considered. After the method is derived, it is applied to a simplified engine mount model in which two elastic beams are coupled through a set of elastic and inertial elements. Just like for the four-pole method, the formulation approach uses building blocks for simple structures that can be assembled to represent more complex structures. Some of the potential applications for this method are also discussed. By using this method, a meaningful characterization of the dynamic behavior can be obtained for structures when the frequency increases beyond that for which the point quantity approaches become invalid.