Assessing the Impact of the Lead/Lag Times on the Project Duration Estimates in Highway Construction

The literature mentions multiple factors that can affect the accuracy of estimating the project duration in highway construction,such as weather,location,and soil conditions.However,there are other factors that have not been explored,yet they can have significant impact on the accuracy of the project time estimate.Recently,TxDOT raised a concern regarding the importance of the proper estimating of the lead/lag times in project schedules.These lead/lag times are often determined based on the engineer’s experience.However,inaccurate estimates of the lead/lag time can result in unrealistic project durations.In order to investigate this claim,the study utilizes four time sensitivity measures(TSM),namely the Criticality Index(CI),Significance Index(SI),Cruciality Index(CRI),and the Schedule Sensitivity Index(SSI)to statistically analyze and draw conclusions regarding the impact of the lead/lag time estimates on the total duration in highway projects.An Excel-based scheduling software was developed with Monte Carlo simulation capabilities to calculate these TSM.The results from this paper show that the variability of some lead/lag times can significantly impact the accuracy of the estimated total project duration.It was concluded that the current practices used for estimating the lead/lag times are insufficient.As such,it is recommended to utilize more robust methods,such as the time sensitivity measures,to accurately estimate the lead/lad times in the projects scheduled.

Social distancing and testing as optimal strategies against the spread of COVID-19 in the Rio Grande Valley of Texas

At the beginning of August 2020,the Rio Grande Valley(RGV)of Texas experienced a rapid increase of coronavirus disease 2019(abbreviated as COVID-19)cases and deaths.This study aims to determine the optimal levels of effective social distancing and testing to slow the virus spread at the outset of the pandemic.We use an age-stratified eight compartment epidemiological model to depict COVID-19 transmission in the community and within households.With a simulated 120-day outbreak period data we obtain a post 180-days period optimal control strategy solution.Our results show that easing social distancing between adults by the end of the 180-day period requires very strict testing a month later and then daily testing rates of 5%followed by isolation of positive cases.Relaxing social distancing rates in adults from 50%to 25%requires both children and seniors to maintain social distancing rates of 50%for nearly the entire period while maintaining maximum testing rates of children and seniors for 150 of the 180 days considered in this model.Children have higher contact rates which leads to transmission based on our model,emphasizing the need for caution when considering school reopenings.

Emergence of instability-driven domains in soft stratified materials

Nature frequently employs the buckling phenomenon to facilitate the formation of complicated patterns across length-scales.Current knowledge,however,is limited to a small set of buckling-induced microstructure transformations in soft composites;and the pattern formation phenomenon remains largely unknown for a vast pool of material morphologies.Here,we investigate the unexplored rich domain of soft heterogeneous composites.We experimentally observe the formation of instability-driven domains in stratified composites with a non-dilute stiff phase.We illustrate that the discovered domain patterns are energetically favorable over wrinkling.Moreover,we introduce a closed-form analytical expression allowing us to predict the evolution of the patterns in the post-buckling regime.Finally,we show that various patterns can be pre-designed via altering material compositions.These findings can help advance our understanding of the mechanisms governing pattern formations in soft biological tissues,and potentially enable the platform for mechanical metamaterials.