Integrated Framework for Quantifying and Predicting Weather-Related Highway Construction Delays

Apipattanavis, Somkiat; Sabol, Kevin; Molenaar, Keith R.; Rajagopalan, Balaji; Xi, Yunping; Blackard, Ben; Patil, Shekhar

doi:10.1061/(asce)co.1943-7862.0000199

Cited by 56 publications

(37 citation statements)

References 10 publications

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“…Wales and AbouRizk (1996) used first-order Markov chains to generate the weather condition, and based on that, activity productivity is estimated by employing a trained neural network. Apipattanavis et al (2010) built an integrated framework for predicting weather (rainfall, temperature, wind speed, and soil temperature) related delays on highway construction project schedules, including a semiparametric multivariate and multisite weather generator and schedule analysis based on CPM. It was assumed that construction delays were uniformly distributed over the entire month.…”

Section: Quantification Of Rainfall Impact On Schedulementioning

confidence: 99%

“…Apipattanavis et al. () built an integrated framework for predicting weather (rainfall, temperature, wind speed, and soil temperature) related delays on highway construction project schedules, including a semiparametric multivariate and multisite weather generator and schedule analysis based on CPM. It was assumed that construction delays were uniformly distributed over the entire month.…”

Section: Introductionmentioning

confidence: 99%

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Earth Dam Construction Simulation Considering Stochastic Rainfall Impact

Zhang

Zhong

et al. 2017

Computer aided Civil Eng

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Effective construction scheme planning is critical for schedule management, but heavy rain can affect construction processes. In previous studies, stochastic rainfall characteristics are often ignored, and their impact on macro‐ and microconstruction states are not depicted comprehensively. This research presents a construction simulation model to design reasonable construction schemes considering impact of stochastic rainfall. First, a rainfall model suitable for areas with heavy rainfall and uneven seasonal rainfall distribution is built. Then, multiaspect indicators are defined to intuitively quantify rainfall impact. Two case studies are conducted to evaluate applicability of the proposed method. Results demonstrate that the developed rainfall model aligns closely with observed data. Simulation findings reveal that if stochastic rainfall characteristics are ignored, the schedule and queuing probability of trucks will be underestimated, while machinery utilization will be overestimated. This research provides an effective simulation tool for determining adaptive measures to mitigate impacts of rainfall events.

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Section: Quantification Of Rainfall Impact On Schedulementioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Earth Dam Construction Simulation Considering Stochastic Rainfall Impact

Zhang

Zhong

et al. 2017

Computer aided Civil Eng

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“…Finally, asphalt pavements are very susceptible to the addition of small quantities of water (in the form of rain, snow or hail) (El-Rayes and Moselhi 2001, Apipattanavis et al 2010, and to extremely high and low temperatures (NCHRP 1978).…”

Section: Combinations Of Weather Variables Affecting Construction Actmentioning

confidence: 99%

Incorporating the effect of weather in construction scheduling and management with sine wave curves: application in the United Kingdom

Ballesteros‐Pérez

Smith

Lloyd-Papworth

et al. 2018

Construction Management and Economics

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The impact of (adverse) weather is a common cause of delays, legal claims and economic losses in construction projects. Research has recently been carried out aimed at incorporating the effect of weather in project planning; but these studies have focussed on either a narrow set of weather variables, or a very limited range of construction activities or projects. A method for processing a country's historical weather data into a set of weather delay maps for some representative standard construction activities is proposed. Namely, sine curves are used to associate daily combinations of weather variables to delay and provide coefficients for expected productivity losses. A complete case study comprising the construction of these maps and the associated sine waves for the UK is presented along with an example of their use in building construction planning. Findings of this study indicate that UK weather extends project durations by an average of 21%. However, using climatological data derived from weather observations when planning could lead to average reductions in project durations of 16%, with proportional reductions in indirect and overhead costs. ARTICLE HISTORY

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“…Decision support tools are widely used in several fields such as operation planning, transport, medicine, finance, environmental resource planning and crisis management at strategic, tactical and operational levels (Jarre et al 2008;Liu and Lai 2009;Acosta et al 2010;Apipattanavis et al 2010;Mensa et al 2011). In these tools, several approaches to risk assessment and automatic decision making are used.…”

Section: Related Work On Environmental Dsssmentioning

confidence: 99%

A maritime decision support system to assess risk in the presence of environmental uncertainties: the REP10 experiment

et al. 2012

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The aim of this work is to report on an activity carried out during the 2010 Recognized Environmental Picture experiment, held in the Ligurian Sea during summer 2010. The activity was the first at-sea test of the recently developed decision support system (DSS) for operation planning, which had previously been tested in an artificial experiment. The DSS assesses the impact of both environmental conditions (meteorological and oceanographic) and nonenvironmental conditions (such as traffic density maps) on people and assets involved in the operation and helps in deciding a course of action that allows safer operation. More precisely, the environmental variables (such as wind speed, current speed and significant wave height) taken as input by the DSS are the ones forecasted by a super-ensemble model, which fuses the forecasts provided by multiple forecasting centres. The uncertainties associated with the DSS's inputs (generally due to disagreement between forecasts) are propagated through the DSS's output by using the unscented transform. In this way, the system is not only able to provide a traffic light map (run/not run the operation), but also to specify the confidence level associated with each action. This feature was tested on a particular type of operation with underwater gliders: the glider surfacing for data transmission. It is also shown how the availability of a glider path prediction tool provides surfacing options along the predicted path. The applicability to different operations is demonstrated by applying the same system to support diver operations.

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Integrated Framework for Quantifying and Predicting Weather-Related Highway Construction Delays

Cited by 56 publications

References 10 publications

Earth Dam Construction Simulation Considering Stochastic Rainfall Impact

Earth Dam Construction Simulation Considering Stochastic Rainfall Impact

Incorporating the effect of weather in construction scheduling and management with sine wave curves: application in the United Kingdom

A maritime decision support system to assess risk in the presence of environmental uncertainties: the REP10 experiment

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