Predicting excess vehicle fuel use due to pavement structural response using field test results and finite element modelling

Estaji, Mostafa; Coleri, Erdem; Harvey, John T.; Butt, Ali Azhar

doi:10.1080/10298436.2019.1655563

Cited by 12 publications

(12 citation statements)

References 20 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The simulated deflection basin, along with the applied 3D contact stresses, were used to calculate excess energy consumption. Studies have suggested that excess energy consumption is a function of pavement structure, material properties, temperature, and vehicle loading ( 9 , 12 , 41 ). Figure 8 shows the computed results at different wheel loads and two pavement temperature profiles.…”

Section: Computation Results and Discussionmentioning

confidence: 99%

“…For example, Zaabar and Chatti ( 7 ) estimated that heavy trucks driven over asphalt pavements consume about 4% more energy than those driven over concrete pavements. It was also reported that the difference in fuel consumption of various classes of vehicles moving on different asphalt pavement structures is around 4%–7% ( 7 – 9 ). However, in these experimental studies, the effect of SRR was difficult to be differentiated from other contributing factors, such as pavement texture and roughness.…”

mentioning

confidence: 99%

See 1 more Smart Citation

Integrated Vehicle–Tire–Pavement Approach for Determining Pavement Structure–Induced Rolling Resistance under Dynamic Loading

Liu

Al-Qadi

2022

Transportation Research Record: Journal of the Transportation R

View full text Add to dashboard Cite

Pavement-related rolling resistances, caused by pavement–vehicle interaction, are important components of pavement life-cycle assessment (LCA). Structure-induced rolling resistance (SRR) is caused by dissipated vehicle kinetic energy in the pavement structure. This paper presents an integrated vehicle–tire–pavement approach to evaluate asphalt pavement SRR under dynamic loading. A three-dimensional (3D) semitrailer-truck model was used to calculate dynamic wheel loads on various pavement surface-roughness profiles. The dynamic wheel loads were then transformed into 3D tire–pavement contact stresses using a deep-learning tire model. Next, an advanced 3D finite element pavement model, validated in previous studies, was used to simulate pavement structure under moving tire–pavement contact stresses. The dynamic load coefficient of axle forces was found to increase linearly with truck speed. The increasing trend became more significant as pavement roughness increased. Ignoring the dynamic loading effect resulted in 12% error in predicting SRR. A case study was performed to illustrate the computation procedures of asphalt pavement SRR under static and dynamic loading. Dynamic loading accounted for 4.74%, 7.37%, 10.73%, and 14.02% of SRR for four pavement surface-roughness levels at a truck speed of 40 mph. In addition, SRR was found to be highly nonlinear and increased as speed decreased and axle load increased. A modified Illinois Center for Transportation SRR model was developed to quickly assess the SRR component of the pavement LCA’s use stage. This study demonstrates the importance of vehicle–tire–pavement interaction in SRR prediction, which may not be overlooked.

show abstract

Section: Computation Results and Discussionmentioning

confidence: 99%

mentioning

confidence: 99%

Integrated Vehicle–Tire–Pavement Approach for Determining Pavement Structure–Induced Rolling Resistance under Dynamic Loading

Liu

Al-Qadi

2022

Transportation Research Record: Journal of the Transportation R

View full text Add to dashboard Cite

show abstract

“…( a ) Hot remixing; ( b ) lift compaction; ( c ) rolling compaction; ( d ) removal of excess binder; ( e ) milling simulation; ( f ) tack coat application; ( g ) coring; ( h ) shear testing prepration; and ( i ) shearing. ( 23 )…”

Section: Laboratory Test Proceduresmentioning

confidence: 99%

“…Adverse field conditions were meticulously simulated in the laboratory to account for conditions such as rainfall, dusty interface, and streaking. The details of the laboratory procedure are explained in the authors’ previous works ( 21 , 23 , 24 ). Table 1 summarizes the factors and the naming convention used in this study.…”

Section: Laboratory Test Proceduresmentioning

confidence: 99%

See 1 more Smart Citation

Investigation of Tack Coat Bond Damage Mechanism in Asphalt Surfaced Pavements under Dynamic Truck Loads

Estaji

Coleri

Wruck

2020

Transportation Research Record: Journal of the Transportation R

Self Cite

View full text Add to dashboard Cite

Bonding created by the tack coat allows the pavement system to carry heavy truck loads as a monolithic structure and improves the structural integrity. In Oregon and throughout the U.S.A., CSS-1H is the most commonly used tack coat type. However, field observations have revealed that new engineered tack coats, although more expensive, outperform the conventional types in relation to shear resistance. In this study, the impact of these new engineered emulsions on in-situ bond performance was quantified by laboratory testing and numerical modeling. Bonding damage performance of all tack coats was experimentally determined by using direct shear tests. Full-scale moving truck load models were developed and calibrated using the load-displacement parameters obtained from the laboratory shear tests. The impact of adverse construction conditions, such as dust, rain, and tack coat coverage, on tack coat bond damage under heavy truck loads was determined. It was concluded that the presence of dust had relatively the lowest contribution to shear damage. Rain during construction had the highest impact on the damage behavior and tack coat application on a wet surface increases the potential for damage by 20.1%. A 50% coverage of tack coat during construction resulted in 12.8% higher damage levels compared with 100% tack coat coverage of the surface area. Moving load models for heavy trucks caused 2.44 times more bonding damage at the bonded interface compared with the damage created by smaller trucks (F450).

show abstract

RolRoad – LCA: A Web-Based Application for Estimating the Excess Fuel Consumption and Environmental Impacts Due to the Rolling Resistance of Passenger Cars

Uva,

Santos,

Cerezo

et al. 2024

RILEM Bookseries

View full text Add to dashboard Cite

Predicting excess vehicle fuel use due to pavement structural response using field test results and finite element modelling

Cited by 12 publications

References 20 publications

Integrated Vehicle–Tire–Pavement Approach for Determining Pavement Structure–Induced Rolling Resistance under Dynamic Loading

Integrated Vehicle–Tire–Pavement Approach for Determining Pavement Structure–Induced Rolling Resistance under Dynamic Loading

Investigation of Tack Coat Bond Damage Mechanism in Asphalt Surfaced Pavements under Dynamic Truck Loads

RolRoad – LCA: A Web-Based Application for Estimating the Excess Fuel Consumption and Environmental Impacts Due to the Rolling Resistance of Passenger Cars

Contact Info

Product

Resources

About