scholarly journals Short-term analysis and long-term predictions for the COVID-19 epidemic in a seasonality regime: the Italian case

2020 ◽  
Author(s):  
Giulia Simoni ◽  
Anna Fochesato ◽  
Federico Reali ◽  
Giulia Giordano ◽  
Enrico Domenici ◽  
...  
Keyword(s):  
Optimization Procedure ◽  
Time Varying ◽  
Short Term ◽  
Italian Case ◽  
Societal Burden ◽  
Second Wave ◽  
Term Analysis ◽  
Time Ease ◽  
Future Outbreak

As of July 14th, COVID-19 has caused in Italy 34.984 deaths and 243.344 infection cases. Strict lockdown policies were necessary to contain the first outbreak wave and prevent the Italian healthcare system from being overwhelmed by patients requiring intensive care. After the progressive reopening, predicting how the epidemic situation will evolve is urgent and fundamental to control any future outbreak and prevent a second wave. We defined a time-varying optimization procedure to repeatedly calibrate the SIDARTHE model with data up to June 24th. The computed parameter distributions allow us to robustly analyse how the epidemic situation evolved and outline possible future scenarios. Assuming a seasonal regime for COVID-19, we tested different lockdown policies. Our results suggest that an intermittent lockdown where six "open days" are allowed every other week may prevent a resurgent exponential outbreak and, at the same time, ease the societal burden of an extensive lockdown.

LOCA analysis of BWR-4/Mark-I nuclear power plant with TRACE

Kerntechnik ◽  
2021 ◽  
Vol 86 (2) ◽  
pp. 128-142
Author(s):  
J.-J. Huang ◽  
S.-W. Chen ◽  
J.-R. Wang ◽  
C. Shih ◽  
H.-T. Lin
Keyword(s):  
Nuclear Power ◽  
Coupled Model ◽  
Short Term ◽  
Containment System ◽  
Loss Of Coolant Accident ◽  
Main Steam Line ◽  
Main Steam ◽  
Temperature Responses ◽  
Term Analysis

Abstract This study established an RCS-Containment coupled model that integrates the reactor coolant system (RCS) and the containment system by using the TRACE code. The coupled model was used in both short-term and long-term loss of coolant accident (LOCA) analyses. Besides, the RELAP5/CONTAN model that only contains the containment system was also developed for comparison. For short-term analysis, three kinds of LOCA scenarios were investigated: the recirculation line break (RCLB), the main steam line break (MSLB), and the feedwater line break (FWLB). For long-term analysis, the dry-well and suppression pool temperature responses of the RCLB were studied. The analysis results of RELAP5/CONTAN and TRACE models are benchmarked with those of FSAR and RELAP5/GOTHIC models, and it appears that the results of the above four models are consistent in general trends.

Strength Performance of Steel Catenary Riser Using Short Term and Long Term Analysis Methodologies

2016 ◽  
Author(s):  
Feng Wang ◽  
Roger Burke ◽  
Anil Sablok ◽  
Kristoffer H. Aronsen ◽  
Oddgeir Dalane
Keyword(s):  
Bending Moment ◽  
Current Profile ◽  
Short Term ◽  
Sea State ◽  
Strength Performance ◽  
Steel Catenary Riser ◽  
Analysis Methodology ◽  
Riser Design ◽  
Term Analysis

Strength performance of a steel catenary riser tied back to a Spar is presented based on long term and short term analysis methodologies. The focus of the study is on response in the riser touch down zone, which is found to be the critical region based on short term analysis results. Short term riser response in design storms is computed based on multiple realizations of computed vessel motions with various return periods. Long term riser response is based on vessel motions for a set of 45,000 sea states, each lasting three hours. The metocean criteria for each sea state is computed based on fifty six years of hindcast wind and wave data. A randomly selected current profile is used in the long term riser analysis for each sea state. Weibull fitting is used to compute the extreme riser response from the response of the 45,000 sea states. Long term analysis results in the touch down zone, including maximum bending moment, minimum effective tension, and maximum utilization using DNV-OS-F201, are compared against those from the short term analysis. The comparison indicates that the short term analysis methodology normally followed in riser design is conservative compared to the more accurate, but computationally more expensive, long term analysis methods. The study also investigates the important role that current plays in the strength performance of the riser in the touch down zone.

scholarly journals The risk for a new COVID-19 wave – and how it depends on R0, the current immunity level and current restrictions

2020 ◽  
Author(s):  
Tom Britton ◽  
Pieter Trapman ◽  
Frank Ball
Keyword(s):  
Preventive Measures ◽  
Reproduction Number ◽  
Social Activity ◽  
Herd Immunity ◽  
Time Varying ◽  
The World ◽  
Two Factors ◽  
Second Wave ◽  
Different Parts ◽  
Future Outbreak

AbstractThe COVID-19 pandemic has hit different parts of the world differently: some regions are still in the rise of the first wave, other regions are now facing a decline after a first wave, and yet other regions have started to see a second wave. The current immunity level î in a region is closely related to the cumulative fraction infected, which primarily depends on two factors: a) the initial potential for COVID-19 in the region (often quantified by the basic reproduction number R0), and b) the timing, amount and effectiveness of preventive measures put in place. By means of a mathematical model including heterogeneities owing to age, social activity and susceptibility, and allowing for time-varying preventive measures, the risk for a new epidemic wave and its doubling time, and how they depend on R0, î and the overall effect of the current preventive measures, are investigated. Focus lies on quantifying the minimal overall effect of preventive measures pMin needed to prevent a future outbreak. The first result shows that the current immunity level î plays a more influential roll than when immunity is obtained from vaccination. Secondly, by comparing regions with different R0 and î it is shown that regions with lower R0 and low î may now need higher preventive measures (pMin) compared with other regions having higher R0 but also higher î, even when such immunity levels are far from herd immunity.

scholarly journals Time-Varying Network Connectedness of G-7 Economic Policy Uncertainties: A Locally Stationary TVP-VAR Approach

2021 ◽  
Vol 7 (2) ◽  
pp. 47-59
Author(s):  
Onur Polat
Keyword(s):  
Economic Policy ◽  
Global Financial Crisis ◽  
Dynamic Networks ◽  
Time Varying ◽  
Short Term ◽  
Frequency Dependent ◽  
Vector Autoregressive ◽  
Network Connectedness ◽  
The Global Financial Crisis

This work analyzes the frequency-dependent network structure of Economic Policy Uncertainties (EPU) across G-7 countries between January 1998 and April 2021. We implement an approach that builds dynamic networks relying on a locally stationary Time-Varying Parameter-Vector Autoregressive model using Quasi-Bayesian Local Likelihood methods. We compute short-, medium-, and long-term network connectedness of G-7 EPUs over a period covering several economic/financial turmoils. Furthermore, we structure short-term network topologies for the Global Financial Crisis (GFC) and the COVID-19 pandemic periods. Findings of the study indicate amplified interdependencies between G-7 EPUs around well-known economic/geopolitical incidents, frequency-dependent connectedness networks among them, and stronger interdependencies than the medium-, and long-term linkages. Finally, we find that short-term spillovers are not persistent in the long-term for both turmoil periods.

Long-term and short-term analysis of the natural rubber market

1989 ◽  
Vol 125 (4) ◽  
pp. 718-747 ◽  
Author(s):  
Kees Burger ◽  
Hidde P. Smit
Keyword(s):  
Natural Rubber ◽  
Short Term ◽  
Rubber Market ◽  
Term Analysis

Representational content determines the long-term dynamics of the CA1 spatial code

2021 ◽  
Author(s):  
Alexandra Keinath ◽  
Coralie-Anne Mosser ◽  
Mark Brandon
Keyword(s):  
Episodic Memory ◽  
Prior Experience ◽  
Representational Content ◽  
Spatial Code ◽  
Time Varying ◽  
Short Term ◽  
Daily Experience ◽  
Neural Ensembles ◽  
Spatial Geometry

Abstract Hippocampal subregion CA1 is thought to support episodic memory by reinstating a stable spatial code. Yet recent experiments have demonstrated that this code is largely unstable on a timescale of days, challenging its presumed function. While these dynamics may indeed reflect homogenous drift within the population, they may alternatively reflect distinct time-varying representational component(s) which coexists alongside other stable components. Here we adjudicate between these possibilities. To this end, we characterized the mouse CA1 spatial code over more than a month of daily experience in an extended geometric morph paradigm. We find that this code is governed by distinct representational components with different long-term dynamics, including stable components representing spatial geometry and prior experience. These components are mediated by separate neural ensembles with similar short-term spatial reliability and precision. Together, these results demonstrate that the long-term dynamics of the CA1 spatial code are defined by representational content, not homogenous drift.

Methods of Computing the Probability of Failure Under Extreme Values of Bending Moment

1972 ◽  
Vol 16 (02) ◽  
pp. 113-123
Author(s):  
Alaa Mansour
Keyword(s):  
Probability Density Function ◽  
Probability Density ◽  
Density Function ◽  
Extreme Values ◽  
Bending Moment ◽  
Random Variable ◽  
Probability Of Failure ◽  
Short Term ◽  
Term Analysis

Methods for predicting the probability of failure under extreme values of bending moment (primary loading only) are developed. In order to obtain an accurate estimate of the extreme values of the bending moment, order statistics are used. The wave bending moment amplitude treated as a random variable is considered to follow, in general, Weibull distribution so that the results could be used for short-term as well as long-term analysis. The probability density function of the extreme values of the wave bending moment is obtained and an estimate is made of the most probable value (that is, the mode) and other relevant statistics. The probability of exceeding a given value of wave bending moment in "n" records and during the operational lifetime of the ship is derived. Using this information, the probability of failure is obtained on the basis of an assumed normal probability density function of the resistive strength and deterministic still-water bending moment. Charts showing the relation of the parameters in a nondimensional form are presented. Examples of the use of the charts for long-term and short-term analysis for predicting extreme values of wave bending moment and the corresponding probability of failure are given.

Characteristic Levels of Strongly Nonlinear Extreme Wave Load Effects

2016 ◽  
Author(s):  
Thomas B. Johannessen ◽  
Øistein Hagen
Keyword(s):  
Wave Breaking ◽  
Nonlinear Problems ◽  
Offshore Structures ◽  
Short Term ◽  
Nonlinear Load ◽  
Load Effect ◽  
Strongly Nonlinear ◽  
Load Effects ◽  
Term Analysis

Offshore structures are typically required to withstand extreme and abnormal load effects with annual probabilities of occurrence of 10−2 and 10−4 respectively. For linear or weakly nonlinear problems, the load effects with the prescribed annual probabilities of occurrence are typically estimated as a relatively rare occurrence in the short term distribution of 100 year and 10 000 year seastates. For strongly nonlinear load effects, it is not given that an extreme seastate can be used reliably to estimate the characteristic load effect. The governing load may occur as an extremely rare event in a much lower seastate. In attempting to model the load effect in an extreme seastate, the short term probability level is not known nor is it known whether the physics of the wave loading is captured correctly in an extreme seastate. Examples of such strongly nonlinear load effects are slamming loads on large volume offshore structures or wave in deck loads on jacket structures subject to seabed subsidence. Similarly, for structures which are unmanned in extreme weather, the governing load effects for the manned structure will occur as extremely rare events in a relatively frequent seastate. The present paper is concerned with the long term distribution of strongly nonlinear load effects. Using a simple point estimate of the wave elevation correct to second order and a crest kinematics model which takes into account the possibility of wave breaking, the long term distribution of drag load on a column above the still water level is studied and compared with a similar loading model based on second order kinematics which does not include the effect of wave breaking. The findings illustrate the challenges listed above. Model tests are useful in quantifying strongly nonlinear load effects which cannot be calculated accurately. But only a relatively small number of seastates can be run in a model test campaign and it is not feasible to estimate short term responses far beyond the three hour 90% fractile level. Similarly, Computational Fluid Dynamics (CFD) is increasingly useful in investigating complex wave induced load effects. But only a relatively small number of wave events can be run using CFD, a long term analysis of load effects cannot in general be carried out. It appears that there is a class of nonlinear problems which require a long term analysis of the load effect in order for the annual probability of occurrence to be estimated accurately. For problems which cannot be estimated by simple analytical means, the governing wave events can be identified by long term analysis of a simple model which capture the essential physics of the problem and then analysed in detail by use of CFD or model tests.

Prediction of Extreme Roll Motion on an FPSO Using Long Term Statistics

2002 ◽  
Author(s):  
Tone M. Vestbo̸stad ◽  
Sverre Haver ◽  
Odd Jan Andersen ◽  
Arne Albert
Keyword(s):  
Probability Distribution ◽  
Wind Waves ◽  
Weather Conditions ◽  
Full Scale ◽  
Roll Motion ◽  
Short Term ◽  
Sea State ◽  
Term Analysis

This paper presents a method for predicting extreme roll motion on an FPSO using long-term statistics. The method consists of a long-term simulation where a database of consecutive short-term sea states with combined weather conditions, including direction and magnitude of wind, wind waves and swell waves, is used. The vessel heading in given weather conditions is simulated. For each combined sea state, the short-term roll motion maxima are calculated to form a long-term probability distribution, and the extreme roll motion, e.g. the 100-year value, can be estimated from the distribution. For an example FPSO, the results from the long-term analysis have been compared with full-scale measurements, giving a validation of the method. This paper is a shortened version of [1].

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