Numerical Approach for Detecting the Resonance Effects of Drilling during Assembly of Aircraft Structures

This paper is devoted to the development of a numerical approach that allows quick detection of the conditions favorable for the beginning of noticeable vibrations during drilling. The main novelty of the proposed approach lies in taking into account the deviations of the assembled compliant parts during non-stationary contact analysis by means of variation simulation. The approaches to stationary analysis of assembly quality are expanded and generalized for modeling such non-stationary effects as vibration and resonance. The numerical procedure is based on modeling the stress–strain state of the assembled structures by solving the corresponding transient contact problem. The use of Guyan reduction, the node-to-node contact model and the application of the generalized α method allow the reformulation of the contact problem in terms of a series of quadratic programming problems. The algorithm is thoroughly tested and validated with commercial software. The efficiency of the developed numerical procedure is illustrated by analysis of the test joints of two aircraft panels. The unsteady process of drilling the panels with periodic drilling force was simulated. The influence of deviations in the shape of the parts on the non-stationary interlayer gap was modeled by setting different initial gaps between parts. It is shown that the oscillation amplitudes of the interlayer gap depend on the initial gaps and do not correlate with the mean value of the stationary residual gap. Thus, non-stationary analysis provides new information about the quality of the assembly process, and it should be applied if the assembly process includes periodic impact on the assembled parts.

Intensity and frequency of extreme novel epidemics

Observational knowledge of the epidemic intensity, defined as the number of deaths divided by global population and epidemic duration, and of the rate of emergence of infectious disease outbreaks is necessary to test theory and models and to inform public health risk assessment by quantifying the probability of extreme pandemics such as COVID-19. Despite its significance, assembling and analyzing a comprehensive global historical record spanning a variety of diseases remains an unexplored task. A global dataset of historical epidemics from 1600 to present is here compiled and examined using novel statistical methods to estimate the yearly probability of occurrence of extreme epidemics. Historical observations covering four orders of magnitude of epidemic intensity follow a common probability distribution with a slowly decaying power-law tail (generalized Pareto distribution, asymptotic exponent = −0.71). The yearly number of epidemics varies ninefold and shows systematic trends. Yearly occurrence probabilities of extreme epidemics, Py, vary widely: Py of an event with the intensity of the “Spanish influenza” (1918 to 1920) varies between 0.27 and 1.9% from 1600 to present, while its mean recurrence time today is 400 y (95% CI: 332 to 489 y). The slow decay of probability with epidemic intensity implies that extreme epidemics are relatively likely, a property previously undetected due to short observational records and stationary analysis methods. Using recent estimates of the rate of increase in disease emergence from zoonotic reservoirs associated with environmental change, we estimate that the yearly probability of occurrence of extreme epidemics can increase up to threefold in the coming decades.

An Empirical Study on Monetary Policy and Economic Growth: The case of Indonesia using an ARDL – ECM Approach

This study explores the role of monetary policy instruments, particularly through the board money supply and inflation, in support of economic growth in Indonesia. The research base on the long-run co-integration approach using the data from 1970 to 2019. The goal of this study complies with applying the Autoregressive Distributed Lag (ARDL), and Error Correction Model (ECM), for finding out the long-run co-integration approach among dependents and independent variables. The research includes the Augmented Dickey-Fuller (ADF) unit root test for stationary analysis. The ECM results show that inflation plays a significant but negative role in economic growth in Indonesia. On the other hand, the money supply has also inversely related to the country's economic growth but not significant

Stationary analysis of infinite queueing system with two - stage network server

As the world's major economies and technologies have matured, they are dominated by service-focused approach leading to study and analysis of service models for improved understanding and efficiency. Research in this direction has been done on various parameters of the finite queues using different approaches. The study discussed in this paper deals with the stationary behavior of two - stage queuing system with infinite capacity where any arriving customer is serviced in two stages in a mutually exclusion fashion. The steady state system size probabilities for the infinite capacity queueing system with two stages of service are obtained in closed form. Further, numerical interpretations are presented to depict the system behavior for values of the parameters.