Adjustment factors for MEPDG pavement responses considering three- dimensional analysis and wide-base tire

The Mechanistic-Empirical Pavement Design Guide (MEPDG) provides a superior methodology as compared to its predecessor in the design and analysis of pavement structures. The mechanistic (MEDPG analysis) calculates critical pavement responses due to pavement-tire interactions. On the other hand, the empirical part refers to the prediction of pavement distress propagation over time using transfer functions. Transfer functions link critical pavement responses to particular pavement distresses. Although MEPDG analysis provides a theoretically framework for pavement simulations, its limitations and simplifications may produce inaccurate pavement response calculations. In contrast, finite element (FE) analysis has proven capable of overcoming these limitations by simulating pavement more realistically in terms of material characterization and loading conditions. However, the high computational cost of the FE analysis precludes its use as a pavement analysis engine within the MEPDG’s framework. Therefore, this study suggests two adjustment factors based on FE analysis to bridge the gap between reality and MEPDG analysis. The first adjustment factor—developed utilizing 480 cases performed in ABAQUS and considering similar material properties and pavement structure—converts pavement responses obtained from dual tire assembly (DTA) loading to new generation wide base tire (NG-WBT) loading. The second adjustment factor—developed from running 336 cases in MEPDG and FE analyses using compatible input parameters—accounts for the limitations of MEPDG analysis regarding the material characterization and loading conditions. The simulated cases were selected to capture extreme conditions—e.g., thick and thin pavement structures with strong and weak material properties—so that extrapolation could be avoided during the implementation of the equations. The adjustment factors revealed that NG-WBT produces higher responses than DTA, which can cause greater pavement damage. Additionally, MEPDG analysis fails to capture the effect of non-uniformity and the three dimensionality of contact stress on pavement response. The discrepancy becomes significant; especially for the pavement responses near the pavement surface, such as tensile strain at the AC surface and vertical shear strain within the AC layer, that are believed to cause top-down cracking

Development of Adjustment Factors for MEPDG Pavement Responses Utilizing Finite-Element Analysis

The Mechanistic-empirical pavement design guide (MEPDG) provides theoretically superior methodology, as compared with its predecessor, for the design and analysis of pavement structures. The mechanistic part refers to simulating pavement–tire interaction to calculate critical responses within pavement. The empirical part means prediction of pavement distress propagation over time using transfer functions that link a critical pavement response to a particular pavement distress. The mechanistic part of MEPDG simulates tire–pavement interaction in three steps: subdivision of pavement layers; complex modulus calculation at the middepth of each sublayer, considering velocity and temperature; and running the multilayered elastic theory (MLET) software, JULEA. Although MEDPG has a grounded methodology for pavement analysis, it has a number of limitations and unrealistic simplifications that result in inaccurate response predictions. These limitations are primarily related to the pavement analysis approach used in the MEPDG framework, MLET. By contrast, finite-element (FE) analysis has proven to be a promising numerical approach for overcoming these limitations and simulating pavement more accurately and realistically. Although comparison of MLET with FE analysis has been studied, the difference between FE and MEPDG simulations has not been quantified. This study fills that gap by developing linear equations that connect pavement responses produced by these two approaches to pavement analysis. The equations are developed for ten different pavement responses, using a total of 336 cases simulated using FE and MEPDG analyses. The cases modeled in simulations were selected to capture extreme conditions, i.e., thick and thin pavement structures with strong and weak material properties. The equations developed can help pavement researchers understand quantitatively the effect of MEPDG limitations. In addition, the equations may be used as adjustment factors for MEPDG to compute pavement responses more realistically without using computationally expensive approaches, such as FE analysis

Optimal Pavement Design and Rehabilitation Planning Using a Mechanistic-Empirical Approach

This paper presents the development of a pavement design and rehabilitation optimization decision-making framework based on Mechanistic-Empirical (ME) roughness transfer models. The AASHTOWare Pavement ME Design (the software of Pavement ME Design) is used to estimate pavement deterioration based on the combined effects of permanent deformation, fatigue, and thermal cracking. The optimization problem is first formulated into a mixed-integer nonlinear programming model to address the predominant trade-off between agency and user costs. To deal with the complexity associated with the pavement roughness transfer functions in the software and to use the roughness values as input to the optimization framework, a dynamic programming subroutine is developed for determining the optimal rehabilitation timing and asphalt concrete design thickness. An application of the proposed model is demonstrated in a case study. Managerial insights from a series of sensitivity analyses on different unit user cost values and model comparisons are presented

Impact of Wide-Base Tires on Pavements: A National Study

This paper summarizes a multi-year effort comparing the new-generation wide-base tires (NG-WBT) and dual-tire assembly from a holistic point of view. The tires were compared considering not only pavement damage but also environmental impact. Numerical modeling, prediction methods, experimental measurements, and life-cycle assessment were combined to provide recommendations about the use of NG-WBT. A finite element (FE) approach considering variables that are usually omitted in the conventional analysis of flexible pavement was used for modeling pavement structures combining layer thickness, material properties, tire load, tire-inflation pressure, and pavement type (interstate and low volume). A prediction tool, ICT-Wide, was developed based on an artificial neural network to obtain critical pavement responses in cases excluded from the FE analysis matrix. Based on the bottom-up fatigue cracking, permanent deformation, and international roughness index, the life-cycle energy consumption, cost, and green-house gas emissions were estimated. To make this research useful for state departments of transportation and practitioners, a modification to AASHTOware is proposed to account for NG-WBT. The revision is based on two adjustment factors, one accounting for the discrepancy between the AASHTOware approach and the FE model of this study, and the other addressing the impact of NG-WBT. Although greater pavement damage may result from NG-WBT, for the analyzed cases, the extra pavement damage may be outweighed by the environmental benefits when NG-WBT market penetration is considered

Reducing the environmental impact of surgery on a global scale: systematic review and co-prioritization with healthcare workers in 132 countries

Abstract Background Healthcare cannot achieve net-zero carbon without addressing operating theatres. The aim of this study was to prioritize feasible interventions to reduce the environmental impact of operating theatres. Methods This study adopted a four-phase Delphi consensus co-prioritization methodology. In phase 1, a systematic review of published interventions and global consultation of perioperative healthcare professionals were used to longlist interventions. In phase 2, iterative thematic analysis consolidated comparable interventions into a shortlist. In phase 3, the shortlist was co-prioritized based on patient and clinician views on acceptability, feasibility, and safety. In phase 4, ranked lists of interventions were presented by their relevance to high-income countries and low–middle-income countries. Results In phase 1, 43 interventions were identified, which had low uptake in practice according to 3042 professionals globally. In phase 2, a shortlist of 15 intervention domains was generated. In phase 3, interventions were deemed acceptable for more than 90 per cent of patients except for reducing general anaesthesia (84 per cent) and re-sterilization of ‘single-use’ consumables (86 per cent). In phase 4, the top three shortlisted interventions for high-income countries were: introducing recycling; reducing use of anaesthetic gases; and appropriate clinical waste processing. In phase 4, the top three shortlisted interventions for low–middle-income countries were: introducing reusable surgical devices; reducing use of consumables; and reducing the use of general anaesthesia. Conclusion This is a step toward environmentally sustainable operating environments with actionable interventions applicable to both high– and low–middle–income countries

Optimization of lateral position of autonomous trucks in a platoon

Introduction of autonomous and connected trucks (ACTs) is expected to result in drastic changes in operational characteristics of freight shipments, which may in turn have significant impacts on efficiency, safety, energy consumption, and infrastructure durability. One such important change is the formation of truck platoons. Truck platoons will become more feasible and practical with the intelligent technologies existing in ACTs that enable the connection among vehicles and between vehicles and infrastructure. Reducing congestion and braking/accelerating and improving fuel efficiency are some of reported and expected benefits of platooning. Yet such platooning operations may accelerate the damage accumulation within pavement structures because the lateral position of successive trucks within a lane is expected to be similar (i.e., channelized traffic) and the time between two consecutive axle loads (i.e., resting time) is expected to be reduced. Therefore, this study develops a platooning-control strategy for a fleet of ACTs such that the lateral position of trucks and spacing between them can be explicitly optimized to minimize damage to the pavement, thus significantly reducing maintenance and rehabilitation costs. In the paper, the efficiency of the proposed strategy was demonstrated through a case study.Ope

Optimization of lateral position of autonomous trucks in a platoon

Introduction of autonomous and connected trucks (ACTs) is expected to result in drastic changes in operational characteristics of freight shipments, which may in turn have significant impacts on efficiency, safety, energy consumption, and infrastructure durability. One such important change is the formation of truck platoons. Truck platoons will become more feasible and practical with the intelligent technologies existing in ACTs that enable the connection among vehicles and between vehicles and infrastructure. Reducing congestion and braking/accelerating and improving fuel efficiency are some of reported and expected benefits of platooning. Yet such platooning operations may accelerate the damage accumulation within pavement structures because the lateral position of successive trucks within a lane is expected to be similar (i.e., channelized traffic) and the time between two consecutive axle loads (i.e., resting time) is expected to be reduced. Therefore, this study develops a platooning-control strategy for a fleet of ACTs such that the lateral position of trucks and spacing between them can be explicitly optimized to minimize damage to the pavement, thus significantly reducing maintenance and rehabilitation costs. In the paper, the efficiency of the proposed strategy was demonstrated through a case study.Ope

Quantitative Assessment of the Effect of Wide-Base Tires on Pavement Response by Finite Element Analysis

Various studies have shown that the new-generation wide-base tire (WBT) for trucks causes more damage to pavement than does the dual-tire assembly (DTA). However, there is no substantive approach that quantifies the difference in pavement responses produced by WBTs and the DTA. This study filled this gap by developing linear equations that connect pavement responses produced by these two tire types. Equations were developed for 10 different pavement responses through 480 finite element method simulations (240 for the DTA and 240 for WBTs) that were run in ABAQUS with the same material properties and pavement structures. The only difference was the contact stresses and contact areas that were measured under the same axle load for WBTs and the DTA. The cases modeled in simulations were selected to capture extreme conditions, that is, thick and thin pavement structures with strong and weak material properties. The equations will help pavement researchers to understand quantitatively the effect of WBTs on pavement responses as compared with the DTA. The low resultant prediction error, 10%, allows linear equations to be implemented through the application of adjustment factors on mechanistic pavement design guides such as the Mechanistic–Empirical Pavement Design Guide, which are unable to simulate WBT loading realistically. To predict pavement damage accurately, the pavement analysis should consider the WBT market penetration in the United States (approximately 10%) and the partial use of WBTs on truck axles. The impact of WBTs on pavement should be evaluated in the context of economic and environmental benefits

Optimal Pavement Design and Rehabilitation Planning Using a Mechanistic-Empirical Approach

This paper presents the development of a pavement design and rehabilitation optimization decision-making framework based on Mechanistic-Empirical (ME) roughness transfer models. The AASHTOWare Pavement ME Design (the software of Pavement ME Design) is used to estimate pavement deterioration based on the combined effects of permanent deformation, fatigue, and thermal cracking. The optimization problem is first formulated into a mixed-integer nonlinear programming model to address the predominant trade-off between agency and user costs. To deal with the complexity associated with the pavement roughness transfer functions in the software and to use the roughness values as input to the optimization framework, a dynamic programming subroutine is developed for determining the optimal rehabilitation timing and asphalt concrete design thickness. An application of the proposed model is demonstrated in a case study. Managerial insights from a series of sensitivity analyses on different unit user cost values and model comparisons are presented