Study of the Influence of Nonlinear Dynamic Loads on Elastic Modulus of Carbonate Reservoir Rocks

The paper presents the results of the experimental investigation of carbonate reservoir rocks subjected to quasistatic and nonlinear dynamic loads. During the quasistatic loading the zones of linear elasticity were determined. Dynamic loading of samples was performed at several frequencies and load amplitudes using a testing system. There were two zones found in which the elastic modulus changes nonlinearly in terms of dynamic load frequency. While the frequency of the dynamic load increases from 0 to 10 Hz the dynamic elastic modulus rises according to logarithmic law; while the frequency increases from 10 to 60 Hz elastic modulus rises according to a power law for each load amplitude. The amplitude of the longitudinal strain and phase shift decreases with increasing frequency of the dynamic load. Under the higher strain rates the rock gets stiffer in comparison with rock subjected to smaller strain rate dynamic loading. Saturation of rock samples with distilled water flattening the dependencies of dynamic Young’s modulus on frequency.

Adding a reaction-restoration type transmission rate dynamic law to the basic SEIR COVID-19 model

The classical SEIR model, being an autonomous system of differential equations, has important limitations when representing a pandemic situation. Particularly, the geometric unimodal shape of the epidemic curve is not what is generally observed. This work introduces the βSEIR model, which adds to the classical SEIR model a differential law to model the variation in the transmission rate. It considers two opposite thrives generally found in a population: first, reaction to disease presence that may be linked to mitigation strategies, which tends to decrease transmission, and second, the urge to return to normal conditions that pulls to restore the initial value of the transmission rate. Our results open a wide spectrum of dynamic variabilities in the curve of new infected, which are justified by reaction and restoration thrives that affect disease transmission over time. Some of these dynamics have been observed in the existing COVID-19 disease data. In particular and to further exemplify the potential the model proposed in this article, we show its capability of capturing the evolution of the number of new confirmed cases of Chile and Italy for several months after epidemic onset, while incorporating a reaction to disease presence with decreasing adherence to mitigation strategies, as well as a seasonal effect on the restoration of the initial transmissibility conditions.

ABOUT ESTIMATION OF THE INFLUENCE OF NON-UNIFORMITY OF INITIAL STATES ON LIFETIME OF FRICTION PAIRS AND TRIBO-FATIGUE SYSTEMS

The article analyzes relationships of the non-uniformity of the initial states and the lifetime of friction pairs and tribo-fatigue systems based on the results of the inspection of the technical condition after operating time and laboratory tests. The non-uniformity of the initial states is determined by the variation within the tolerances of the geometry of the elements due to the manufacturing technology, and its influence on the wear rate, dynamic characteristics and lifetime of mechanical systems is estimated on the example of automobile sliding friction bearing pairs and rolling bearings. A laboratory experiment to assess the performance of a model of a tribo-fatigue system “shaft (steel 45) — roller (25ХГТ (25KhGT) steel)” due to local violation of the shaft geometry during rolling is analyzed. The correlation equations are given that link the integral characteristics of the local process of wear-fatigue damage, based on measurements of the circular contour of the test specimen (coefficients of asymmetry and non-uniformity), with the relative number of cycles until the limiting wear of the tribo-fatigue system “shaft (steel 45) — liner (silumin)” under sliding friction is reached.

Real-Time Model Updating Algorithm for Structures Experiencing High-Rate Dynamic Events

Real-time model updating of active structures subject to unmodeled high-rate dynamic events require structural model updates on the timescale of 2 ms or less. Examples of active structures subjected to unmodeled high-rate dynamic events include hypersonic vehicles, active blast mitigation, and orbital infrastructure. Due to the unmodeled nature of the events of interest, the real-time model updating algorithm should circumvent any model pre-calculations. In this work, we present a methodology that updates the finite element analysis (FEA) model of a structure experiencing varying dynamics through online measurements. The algorithm is demonstrated for a testbed, comprised of a cantilever beam and a roller that serves as movable support. The structure’s state is updated (i.e. the position of the moving roller) by continuously updating the associated FEA model through an online adaptive meshing and search algorithm. The structure’s state is continuously estimated by comparing the measured signals with FEA models. New FEA models are built based on the enhanced estimate of the structure’s state through adaptive meshing for modal analysis and adaptive search space for the FEA model selection. The proposed methodology is verified experimentally in real-time using the testbed. It is demonstrated that the adaptive features can achieve accurate state estimations within the required 2 ms timescale.

A Comparison of Time-Frequency Methods for Real-Time Application to High-Rate Dynamic Systems

High-rate dynamic systems are defined as engineering systems experiencing dynamic events of typical amplitudes higher than 100 gn for a duration of less than 100 ms. The implementation of feedback decision mechanisms in high-rate systems could improve their operations and safety, and even be critical to their deployment. However, these systems are characterized by large uncertainties, high non-stationarities, and unmodeled dynamics, and it follows that the design of real-time state-estimators for such purpose is difficult. In this paper, we compare the promise of five time-frequency representation (TFR) methods at conducting real-time state estimation for high-rate systems, with the objective of providing a path to designing implementable algorithms. In particular, we examine the performance of the short-time Fourier transform (STFT), wavelet transformation (WT), Wigner–Ville distribution (WVD), synchrosqueezed transform (SST), and multi-synchrosqueezed transform (MSST) methods. This study is conducted using experimental data from the DROPBEAR (Dynamic Reproduction of Projectiles in Ballistic Environments for Advanced Research) testbed, consisting of a rapidly moving cart on a cantilever beam that acts as a moving boundary condition. The capability of each method at extracting the beam’s fundamental frequency is evaluated in terms of precision, spectral energy concentration, computation speed, and convergence speed. It is found that both the STFT and WT methods are promising methods due to their fast computation speed, with the WT showing particular promise due to its faster convergence, but at the cost of lower precision on the estimation depending on circumstances.