Curve Fitting Free-Vibration Time Response for Estimation of Structural Dynamic Parameters

Hallauer, W. L.; Slemp, Wesley C. H.; Kapania, Rakesh K.

doi:10.1111/j.1747-1567.2008.00449.x

Cited by 6 publications

(4 citation statements)

References 6 publications

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“…We have estimated parameters by fitting to available COVID-19 data from the official websites of Ministry of Health in each country. The function for the fitting is Matlab’s function lsqcurvefit (27) and the code was derived from E. Cheynet et al (28). Modified SPIERQD Model 2 presented in following equations:…”

Section: Methodsmentioning

confidence: 99%

COVID-19 Outbreak in Post-Soviet States: Modeling the Best and Worst Possible Scenarios

Abbay

Adambekov

Aljofan

et al. 2020

Preprint

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Background: COVID-19 pandemic has presented extreme challenges to developing countries across the world. Post-Soviet states are facing unique challenges due to their developing healthcare systems and unstable economy. The aim of this paper was to provide estimates for current development COVID-19 pandemic in the Post-Soviet states and forecast potential best and worst scenarios for spread of this deadly infection. Methods:The data on confirmed cases and deaths were extracted from official governmental sources for a period from beginning of outbreak dates for each country until April 18, 2020. A modified SEIR (Susceptible-Exposed-Infected-Recovered) modelling was used to plot the parameters of epidemic in 10 post-Soviet states and forecast the number of cases over a period of 10, 30 and 60 days. We also estimated the numbers of cases based on the optimal measures (best scenario) and suboptimal measures (worst scenarios) of potential spread of COVID-19 in these countries.

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Section: Methodsmentioning

confidence: 99%

COVID-19 Outbreak in Post-Soviet States: Modeling the Best and Worst Possible Scenarios

Abbay

Adambekov

Aljofan

et al. 2020

Preprint

View full text Add to dashboard Cite

show abstract

“…We have estimated parameters by fitting to available COVID-19 data from the official websites of Ministry of Health in each country. The function for the fitting is Matlab's function lsqcurvefit (29) where t represents number of days.…”

Section: Numerical Simulationsmentioning

confidence: 99%

COVID-19 Outbreak in Post-Soviet States: Modeling the Best and Worst Possible Scenarios

et al. 2020

View full text Add to dashboard Cite

Background: COVID-19 pandemic has presented extreme challenges to developing countries across the world. The aim of this paper was to provide estimates for current development COVID-19 pandemic in the Post-Soviet states and forecast potential best and worst scenarios for spread of this deadly infection. Methods:The data on COVID-19 cases extracted from official governmental sources until April 18, 2020. A modified SEIR (Susceptible-Exposed-Infected-Recovered) modelling was used to plot the pandemic outbreak in 10 Post-Soviet states and forecasting over the period of 10, 30 and 60 days. The optimal measures (best-scenario) and suboptimal measures (worst-scenarios) of potential spread of COVID-19 in these countries were estimated.Results: It was estimated that Armenia and Azerbaijan have reached their peaks, Kazakhstan, Kyrgyzstan, Moldova, and Uzbekistan are expected to reach their peaks in the early May-2020), with comparatively low cases of COVID-19 in the best-case scenario. In contrast, Belarus, Russia, and Ukraine would likely see the outbreaks with the largest number of COVID-19 cases amongst the studied Post-Soviet States in the worst-scenario during the next 30 and 60 days. Conclusion:Governmental response was shown to be as an important determining factor responsible for the development of COVID-19 epidemic in Post-Soviet states. The current protection rates should be maintained to reduce active cases during upcoming 30 and 60 days. The estimated possible scenarios based on the proposed model can potentially be used by healthcare professionals from each studied Post-Soviet States as well as others to improve plans to contain the current and future epidemic.

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“…A damping ratio of 0.008 was used for the analytical model. This value was extracted by curve fitting the reference accelerometer signal [22]. The analytical rotational and translational FRFs can be obtained and compared to the EMA results.…”

Section: Analytical Cantilever Beam Modelingmentioning

confidence: 99%

Non-contact experimental modal analysis using air excitation and a microphone array

et al. 2010

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Curve Fitting Free-Vibration Time Response for Estimation of Structural Dynamic Parameters

Cited by 6 publications

References 6 publications

COVID-19 Outbreak in Post-Soviet States: Modeling the Best and Worst Possible Scenarios

COVID-19 Outbreak in Post-Soviet States: Modeling the Best and Worst Possible Scenarios

COVID-19 Outbreak in Post-Soviet States: Modeling the Best and Worst Possible Scenarios

Non-contact experimental modal analysis using air excitation and a microphone array

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