Asteroid phase curves using sparse and dense photometry

<p align="justify">We present a phase-curve computation method capable of combining sparse survey data, like relative photometry with dense differential measurements. Combining those types of data allows to obtain phase-curves parameters for large number of asteroids for which using traditional approach would not be sufficient.</p> <p align="justify">Using traditional dense ground-based photometry collected at Astronomical Observatory Institute of Adam Mickiewicz University in Poznań alongside with absolute Gaia measurements we were able to perform more accurate lightcurve amplitude correction and then derive the phase-slope parameter β of the phase-curve separately for each opposition which met our selection criteria. We show preliminary results for 31 oppositions of 24 asteroids.</p> <p align="justify">In the future we plan to create a large photometric database containing sparse and dense photometry from various publicly available data sources (Gaia, ATLAS, K2, LSST, TESS, VISTA and others) which will include absolute, relative and differential photometry.</p> <p align="justify"><strong>Acknowledgments: </strong>This work has been supported by grant No. 2017/25/B/ST9/00740 from the National Science Centre, Poland.</p>

An algorithm to simulate nonstationary and non-Gaussian stochastic processes

We proposed a new iterative power and amplitude correction (IPAC) algorithm to simulate nonstationary and non-Gaussian processes. The proposed algorithm is rooted in the concept of defining the stochastic processes in the transform domain, which is elaborated and extend. The algorithm extends the iterative amplitude adjusted Fourier transform algorithm for generating surrogate and the spectral correction algorithm for simulating stationary non-Gaussian process. The IPAC algorithm can be used with different popular transforms, such as the Fourier transform, S-transform, and continuous wavelet transforms. The targets for the simulation are the marginal probability distribution function of the process and the power spectral density function of the process that is defined based on the variables in the transform domain for the adopted transform. The algorithm is versatile and efficient. Its application is illustrated using several numerical examples.

Calibrating the 2016 IRIS Wavefields Experiment Nodal Sensors for Amplitude Statics and Orientation Errors

ABSTRACT We used teleseismic P and S waves recorded in the course of the 2016 Incorporated Research Institutions for Seismology (IRIS) community-planned experiment in northern Oklahoma, to estimate amplitude correction factors (ACFs) and orientation correction factors (OCFs) for the gradiometer’s three-component Fairfield nodal sensors and two other gradiometer-styled subarray nodal sensors. These subarrays were embedded in the 13 km aperture nodal array that was also fielded during the 2016 IRIS experiment. The array calibration method we used in this study is based on the premise that a common wavefield should be recorded over a small-aperture array using teleseismic observation. In situ estimates of ACF for the gradiometer vary by 2.3% (standard deviation) for the vertical components and, typically, variability is less than 4.3% for the horizontal components; associated OCFs generally dispersed by 3°. For the two subarrays, the vertical-component ACF usually vary up to 2.4%; their horizontal-component ACFs largely spread up to 3.6%. OCFs for the subarrays generally disperse by 6.5°. ACF and OCF estimates for the gradiometer are seen to be stable across frequency bands having high signal coherence and/or signal-to-noise ratio. Gradiometry analyses of calibrated and uncalibrated gradiometer records from a local event revealed notable improvements in accuracy of attributes obtained from analyzing the calibrated horizontal-component waveforms in the light of catalog epicenter-derived azimuth. The improved waveform relative amplitudes after calibration, coupled with the enhanced wave attribute accuracy, suggests that instrument calibration for amplitude statics and orientation errors should be encouraged prior to doing gradiometry analysis in future studies.

INCEFA-PLUS Project: The Impact of Using Fatigue Data Generated From Multiple Specimen Geometries on the Outcome of a Regression Analysis

The INCEFA-PLUS project (INcreasing Safety in NPPs by Covering gaps in Environmental Fatigue Assessment) aims to generate and analyse Environmentally-Assisted Fatigue (EAF) experimental data studying parameters such as mean strain, hold times and surface finish. To understand the implications of these parameters for environmental fatigue assessments, these tests were carried out at 300 °C in air and light water reactor primary coolant environments (at 230 °C and 300 °C). Over the duration of this project around 230 fatigue data points were generated by different organisations using a common testing methodology, but with differing specimen geometries. Of these 230 data points, 23 were obtained from tests done using hollow specimen designs. Recent work comparing the fatigue lives of hollow to those of solid specimens indicates that on average the use of hollow specimens results in reduced fatigue lives. This has been explained in terms of the additional hoop and radial strains applied to the specimen due to the internal pressure of the hollow specimen. Given the examples published in the literature on the topic, the comparison of data generated using hollow and solid specimen geometries within the INCEFA-PLUS database has been a particular concern. This paper aims to explore the differences between hollow and solid specimen geometries within the INCEFA-PLUS database, highlight the potential risks of including both geometries in a single analysis, and discusses the approach taken by the project to mitigate the identified risks. The work presented in this paper details three approaches for the data obtained from hollow specimens: 1) exclude the data, 2) include the data as is, or 3) include the data with a correction on the strain amplitude. The strain amplitude correction will be based on the theoretical basis presented in Gill et al. [1], and extended to account for the different hollow specimen geometries used across the INCEFA-PLUS programme. This work demonstrates the robustness of the data analysis performed on the INCEFA-PLUS database to the use of differing specimen geometries. It also develops an explanation for the apparent difference in fatigue life between tests conducted on hollow and solid specimens under test conditions that are nominally the same. Furthermore, this paper builds on the mechanistic understanding presented in Gill et al. [1] and generalises across several Laboratories.

Rotary machine vibration monitoring and smart balance correction

During the rotary machine operation process, seemingly small amounts of abnormal vibration can often cause serious damage to the machinery over time and even increase the risk of accidents. Although professional vibration engineers can determine the current health status of a machine by interpreting the vibration spectrum information and predicting which components will fail, if even ordinary operators can send feedback regarding the vibration signals reaching the human–machine interface through a system when an abnormality is detected in the machine, the abnormality can be made known and processed in time. This can prevent the magnified impact of rotary inertia, thereby lowering the risk of major damage and the failure of machinery and equipment, as well as effectively saving on equipment maintenance costs. This study mainly adopted LabVIEW and Arduino IDE to develop a control program and human–machine monitoring interface. As the initial experiment on rotary machine vibration monitoring and smart balance correction, the measurement system setup in this study was applied to determine vibration abnormality as well as to carry out continuous online automatic balance correction. Experimental verification was carried out using active correction and smart correction. In terms of active online balance correction, the amplitude correction rate was 96%, the double-frequency correction rate was 102.9%, and the correction process was performed in 5 min. In terms of smart balance correction, the amplitude correction rate was 103.8%, the double-frequency correction rate was 103.3%, and the correction process was performed in 3 min. Through feedback signaling, the operator can effectively learn the current health status of the mechanical equipment from the human–machine interface.

Analysis of Wave Patterns Under the Region of Macro-Fiber Composite Transducer to Improve the Analytical Modelling for Directivity Calculation in Isotropic Medium

Analytical modelling is an efficient approach to estimate the directivity of a transducer generating guided waves in the research field of ultrasonic non-destructive testing of the large and complex structures due to its short processing time as compared to the numerical modelling and experimental techniques. The wave patterns or the amplitude variations along the region of ultrasonic transducer itself depend on its behavior, excitation frequency, and the type of propagating wave mode. Depending on the wave-pattern of a propagating wave mode, the appropriate value of the amplitude correction factor must be multiplied to the amplitudes of the excitation signal for the accurate evaluation of directivity pattern of the ultrasonic transducers generating guided waves in analytical modelling. The objective of this work is to analyse the wave patterns under the region of macro-fiber composite (MFC) transducer to improve the accuracy of a previously developed analytical model for the prediction of directivity patterns. Firstly, the amplitude correction factor based on the wave patterns under the region of P1-type MFC (MFC-2814) transducer at two different frequencies (80 kHz, 3 periods and 220 kHz, 3 period) glued on 2 mm Al alloy plate has been estimated analytically in the case of an asymmetric (A0) guided Lamb wave. The validation of analytically estimated amplitude correction factor is performed by a proposed experimental method that allows analyzing the behaviour of MFC transducer under its region by gluing MFC on bottom surface and scanning the receiver on the top surface of the sample. Later on, the estimated amplitude correction factor is included in the previously developed 2D analytical model for the improvement in the directivity patterns of the A0 mode. The modified analytical model shows a significant improvement in the directivity pattern of the A0 wave mode in comparison to the results obtained by the previous model without considering the proper wave patterns. The results reveal that errors between the directivity estimated by the present modified 2D analytical model and experimental investigation are reduced by more than 58% in comparison to the previously developed analytical model.