Pavement Temperature Research Articles

Study on cohesion and adhesion behaviors of the zeolite foamed asphalt-warm mix mixture based on molecular dynamics simulation

Zeolite foamed asphalt - warm mix mixture (ZFA-WMM) has been applied in large quantities in asphalt pavement, however, a lower construction temperature, residual zeolite water and zeolite minerals have different effects on the cohesion and adhesion properties of zeolite foamed asphalt (ZFA), which indirectly affects the water stability of its mixture. This study analyzed the interface behavior in ZFA-WMM using molecular dynamics simulation. First, the molecular model of ZFA was constructed, and its thermodynamic properties were calculated and compared with experimental values and related simulated values to validated the reasonable of model. Then, the interface models of ZFA-aggregate (quartz and calcite) and ZFA-ZFA were established, simulating the effects of the zeolite mineral dosage, temperature, and interface moisture (residual zeolite water) content on the cohesion and adhesion of ZFA. Furthermore, the occurrence mode of cohesion or adhesion failures in ZFA-WMM were predicted by comparing the ZFA-aggregate adhesion work with ZFA cohesion work. The simulation results indicated that as the zeolite mineral dosage increased, the ZFA cohesion and ZFA-calcite adhesion increased, while ZFA-quartz adhesion first grew and then dropped, reaching its maximum at 9.4 % zeolite mineral dosage. Under the pavement operating temperature range (-15°C∼65°C), higher pavement temperatures are beneficial to ZFA-aggregate adhesion; the cohesion of ZFA first increases and then decrease as temperature rises, reaching its maximum at 25℃. The larger the interface moisture content, the higher the possibility of water separating ZFA from the aggregate surface and the water sensitivity of ZFA-WMM. The ZFA-WMM is prone to adhesion failure, especially at higher zeolite dosages.

Effects of Thermo-Chromic materials (TCMs) on the performance of asphalt pavement with phase change materials (PCMs)

Temperature regulation is crucial for the longevity of pavements. Thermo-Chromic Materials (TCMs) is proposed for effective temperature regression in pavements with Phase Change Materials (PCMs). In this paper, the performance of asphalt pavements in a typical year is investigated with Abaqus, including the peak temperature, the variation of surface temperature and the properties of PCMs before and after the adoption of TCMs. The incorporation of PCMs resulted in a reduction of peak pavement temperatures by 1.3 °C, while the addition of TCMs further decreased temperatures by 38.5 °C. By comparison with the results with and without PCMs as well as with and without TCMs, it is concluded that both PCMs and TCMs may reduce the peak temperature of asphalt pavements. However, TCMs may further regress the peak temperature but does not result in the time delay of peak temperature, as PCMs does. The peak temperature positively correlates with the variation of surface temperature. Nevertheless, although only four types of correlation between the temperature property of TCMs and that of PCMs are involved, the profile or status of PCMs is much more complicatedly influenced after the adoption of TCMs, indicating the interaction between TCMs and PCMs. More time of PCMs is in the phase of solid, due to the modulation of solar radiation. As far as the peak temperature is considered, it is also possible to reduce the amount of PCMs applied in pavements, with the adoption of TCMs. According to the results in this paper, the application of TCMs in an asphalt pavement with PCMs may be an effective way to reduce the peak temperature, to regress the daily variation degree as well as to improve the performance of PCMs.

Real-time pavement temperature prediction through ensemble machine learning

Pavement temperature is crucial for assessing asphalt pavement's performance and structural integrity due to its viscoelastic behavior. Currently, asphalt temperature prediction includes analytical, numerical, and statistical methods and relies on field investigation with intensive labor and time to hinder routine practice. Machine learning (ML) offers a promising solution for reliable and accurate real-time predictions by considering various dynamic environmental factors. This research employs four ensemble ML algorithms: eXtreme Gradient Boosting (XGB), Light Gradient Boosting Machine (LGBM), Random Forest (RF), and Adaptive Boosting (AdaBoost) to predict pavement temperature at different depths. XGB consistently outperformed other ensemble models, boasting the highest average R2 value (97.92%) and lower MAE and RMSE than LGBM, RF, and AdaBoost. XGB also significantly outperformed other commonly used models (linear regression, SVR, ANN, LSTM, and GRU) with an average reduction in errors of 35.29%, 63.75%, 42.75%, and an increase in R2 by 4.39% for MAE, MSE, RMSE, and R2, respectively. The Shapley additive explanation (SHAP) was applied to interpret the underlying influencing factors and their interactions, and revealed atmospheric temperature as the most impactful feature, contributing over 40.58% among the significant features.Furthermore, the predictive performance of XGB was enhanced by incorporating Principal Component Analysis to reduce computational consumption with average reductions of 8.98%, 16.59%, 9.01%, and 7.89% in MAE, MSE, MAPE, and RMSE. XGB with PCA emerges as the most effective and efficient model for predicting pavement temperatures at various depths to facilitate timely decision-making for preventive maintenance and rehabilitation and prevent future catastrophic failures.

Optical responsive asphalt coating with temperature-sensitive TiO2 quantum dots: Formula and temperature adaptability

The application of conventional asphalt contributes to extremely high pavement temperature in hot season as its black color entails large solar absorption. In this study, optical responsive asphalt is proposed to control pavement temperature, which is developed by introducing temperature-sensitive TiO2 quantum dots (TiO2 QDs) into traditional asphalt. Temperature-sensitive TiO2 QDs are prepared by blending thermochromic polymer and TiO2 quantum dots with varied concentrations. Optical characterizations on temperature-sensitive TiO2 QDs have demonstrated that peak value of solar absorption in temperature-sensitive TiO2 QDs at 45 °C is 14.29 %–22.86 % higher than that at 15 °C; the maximum fluorescent intensity of temperature-sensitive TiO2 QDs at 45 °C is 8.5 % higher than that at 15 °C. The results from optical characterizations on temperature-sensitive TiO2 QDs modified asphalt show that the incorporation of temperature-sensitive TiO2 quantum dots endows asphalt low solar reflectance at high temperature and high solar absorption at low temperature. Fluorescent intensity of modified asphalt at 45 °C is increased by 21.6 %, 10.2 % and 5.7 % than that at 15 °C for asphalt containing 5 %, 10 %, and 20 % temperature-sensitive TiO2 QDs, respectively. Indoor solar radiation simulation tests have revealed that compared with traditional asphalt, temperature-sensitive TiO2 QDs modified asphalt coating could yield cooling effectiveness of 6.4 °C at high temperature. Meanwhile, outdoor solar radiation test indicates TiO2 QDs modified asphalt coating could realize warming effectiveness of 0.7 °C at low temperature. The outcomes on temperature-sensitive TiO2 QDs modified asphalt with temperature-adaptability properties makes an advancement in functional pavement.

Cooling characteristics of thermochromic powder modified sand fog seal on asphalt pavement in summer high-temperature environment

Reversible optical response can occur in thermochromic materials with temperature changes, which has great potential in the field of pavement temperature regulation. The thermochromic sand fog seal (TP-SFS) was proposed in this study, which has the functions of pavement repair and temperature control. In this study, different types (red, blue, black) and contents (0 %, 2 %, 4 %, 6 %, and 8 %) of thermochromic powders (TP) were used to prepare TP-SFS. Secondly, the cooling characteristics of different TP-SFS was explored from the perspectives of temperature change rate, cooling temperature, and temperature gradient, based on the designed indoor and outdoor multi-cycle illumination test. Then, the prediction model of the outdoor cooling effect was proposed. In addition, the conservation and environmental benefits of different TP-SFS were calculated according to the empirical formula. It is found that after spraying TP-SFS, the heating rate of pavement decreases and the cooling rate increases. The cooling effect at 2 cm depth of the pavement sprayed with TP-SFS is the most significant, and the temperature gradient of the pavement is reduced. The cooling temperature of the pavement increases with the increase of TP content. In the outdoor environment, the more obvious cooling effect occurs as the process of pavement temperature increases and decreases. Additionally, the reliability of the designed indoor test is high, and the cooling effect of TP-SFS in outdoor environment can be well predicted according to the proposed model. The results of empirical formula calculation show that TP-SFS has a significant effect on delaying rutting development and alleviating urban heat island effect.

Application of the Machine Learning Method to Determine Spring Load Limits and Winter Weight Premium

Freight transportation plays a crucial role in sustaining the Canadian economy. However, heavy truck transportation also puts enormous pressure on roadway networks. Spring Load Restrictions (SLR) are implemented to minimize road damage caused by heavy traffic during the thaw-weakening season, and Winter Weight Premium (WWP) is used to reduce the impact of SLR on trucking operations by allowing higher axle loads in winter. However, existing policies apply fixed dates each year for these restrictions, regardless of the actual structural capacity of the pavement. Different methods have been proposed to improve the application of SLR and WWP; however, they rely mainly on indirect indices, such as the cumulative thawing index and cumulative freezing index, which pose challenges in their calculation. This study explores the practical implementation of machine learning models for accurately determining the start and end dates of SLR and WWP. In a novel approach, machine learning models directly derive the start and end dates of SLR and WWP from frost and thaw depths in the pavement structure which are determined by pavement temperature and moisture content. In contrast to previous studies that neglected the influence of soil moisture content on determining the start and end dates of SLR and WWP, this study examines the variation in soil moisture content to evaluate the validity of existing theories. The findings reveal a high level of agreement between the machine learning model’s estimations of frost and thaw depths and the measured values, with R2 values exceeding 0.91.

Development of Asphalt Pavement Temperature Prediction Models for Sub-Saharan Tropical Climate: The Case of Ghana

Development of Asphalt Pavement Temperature Prediction Models for Sub-Saharan Tropical Climate: The Case of Ghana

An Overview of Phase Change Materials and Their Applications in Pavement

The composite of a phase change material (PCM) and bitumen or asphalt as a matrix is expected as a new, advanced material for road construction. The main motivation for this article was to show the new possibilities and perspectives of developing the pavement with the usage of PCMs. Incorporating PCMs into paving materials can improve their properties, including allowing the regulation of the pavement temperature, enhancement of the pavement durability, and avoiding the phenomenon of a heat-island on the road. The main purpose of this article was to evaluate contemporary investigations in the area of the application of PCMs in pavement materials, especially asphalt and bitumen; to summarize the advantages and disadvantages of the implementation of PCM for road construction; and to discuss further trends in this area. This manuscript explored the state of the art in this area based on research in the literature. It shows the possible material solutions, presenting their composition and discussing their key properties and the manufacturing technologies used. The possibilities for further implementations are considered, especially economic issues.

An innovative simplified approach for conductive heat flux in pavement structures

Understanding the conductive heat flux at pavement surfaces and interior layers is crucial for reducing pavement distress, developing cooler pavements, and mitigating urban heat island (UHI) effects. Existing methods often rely on calculating the conductive heat flux as the residual heat flux from net radiation and heat convection, leading to significant measurement uncertainties in practice. This study overcomes this issue by introducing a novel model based on Maclaurin polynomial temperature profiles to more accurately determine the conductive heat flux across pavement surfaces and depths. Validated against designed experiments and existing literature, our model shows that both cubic and quadratic Maclaurin polynomials can approximate pavement temperature profiles properly. Our model facilitates the determination of conductive heat flux at various pavement depths, including the surface. By correlating the temperature gradient with measured conductive heat flux at specific depths, we accurately determine the thermal conductivity of the pavement. The proposed method more accurately estimates conductive heat flux compared to the traditional residual methods. The model proves useful in quantifying conductive heat flux, convection, and convection coefficients at various pavement locations, offering enhanced monitoring of conductive heat flux across urban streets.

Investigating Road Ice Formation Mechanisms Using Road Weather Information System (RWIS) Observations

Ice formation on roads leads to a higher incidence of accidents and increases winter de-icing/anti-icing costs. This study analyzed 3 years (2019–2021) of Road Weather Information System (RWIS) sub-hourly measurements collected by the Montana Department of Transportation (MDT) to understand the first-order factors of road ice formation and its mechanisms. First, road ice is formed only when the road pavement surface temperature is equal to or below the freezing point (i.e., 32 °F (i.e., 0 °C)), while the corresponding 2 m air temperature could be above 32 °F. Nevertheless, when the road pavement was below 32 °F ice often did not form on the roads. Therefore, one challenge is to know under what conditions road ice forms. Second, the pavement surface temperature is critical for road ice formation. The clear road (i.e., with no ice or snow) surface pavement temperature is generally warmer than the air temperature during both day and night. This feature is different from a natural land surface, where the land skin temperature is lower than the air temperature on cloud-free nights due to radiative cooling. Third, subsurface temperature, measured using a RWIS subsurface sensor below a road surface, did not vary as much as the pavement temperature and, thus, may not be a good index for road ice formation. Fourth, urban heat island effects lead to black ice formation more frequently than roads located in other regions. Fifth, evaporative cooling from the water surface near a road segment further reduces the outlying air temperature, a mechanism that increases heat loss for bridges or lake-side roads in addition to radiative cooling. Additionally, mechanical lifting via mountains and hills is also an efficient mechanism that makes the air condense and, consequently, form ice on the roads. Forecasting road ice formation is in high demand for road safety. These observed features may help to develop a road ice physical model consisting of functions of hyper-local weather conditions, local domain knowledge, the road texture, and geographical environment.

RHEOLOGICAL CHARACTERIZATION OF TRANSPARENT ASPHALT MODIFIED WITH COLORING PIGMENTS

The black asphalt is high-temperature dependent and viscoelastic in nature, which is prone to experiencing more significant rutting under vehicular loading conditions when exposed to high temperatures. In addition, the pavement temperature contributes towards urban heat island (UHI). Therefore, colored pavement surfaces could play a role in protecting asphalt pavements from excessive rutting. This study investigated the use of transparent asphalt colored with green iron pigment as an alternate asphalt for replacing traditional black asphalt. The paper studied the rheological properties of a transparent asphalt modified with 4% by weight green pigment. The experiment included the determinations of penetration values, softening point temperatures, rotational viscosity, and rutting parameters (G*/sin δ). The AASHTOW Pavement MEPDG Design software was utilized to assess the impact of using transparent and colored asphalt on the simulated rutting performance under Sharjah climate conditions. The study's findings indicated that the transparent and colored asphalt demonstrated superior rheological characteristics compared to black asphalt. The rutting parameter of colored and transparent asphalt was greater than that of the black asphalt. Finally, simulated rutting analysis showed that both transparent and colored asphalt binders exhibited better resistance against long-term rutting performance compared to black asphalt.

RHEOLOGICAL CHARACTERIZATION OF TRANSPARENT ASPHALT MODIFIED WITH COLORING PIGMENTS

The black asphalt is high-temperature dependent and viscoelastic in nature, which is prone to experiencing more significant rutting under vehicular loading conditions when exposed to high temperatures. In addition, the pavement temperature contributes towards urban heat island (UHI). Therefore, colored pavement surfaces could play a role in protecting asphalt pavements from excessive rutting. This study investigated the use of transparent asphalt colored with green iron pigment as an alternate asphalt for replacing traditional black asphalt. The paper studied the rheological properties of a transparent asphalt modified with 4% by weight green pigment. The experiment included the determinations of penetration values, softening point temperatures, rotational viscosity, and rutting parameters (G*/sin δ). The AASHTOW Pavement MEPDG Design software was utilized to assess the impact of using transparent and colored asphalt on the simulated rutting performance under Sharjah climate conditions. The study's findings indicated that the transparent and colored asphalt demonstrated superior rheological characteristics compared to black asphalt. The rutting parameter of colored and transparent asphalt was greater than that of the black asphalt. Finally, simulated rutting analysis showed that both transparent and colored asphalt binders exhibited better resistance against long-term rutting performance compared to black asphalt.

Distribution fitting and ANOVA test to analyze pavement sensing patterns for condition assessments

Purpose The purpose of this paper is to investigate the vehicle-based sensor effect and pavement temperature on road condition assessment, as well as to compute a threshold value for the classification of pavement conditions.Design/methodology/approach Four sensors were placed on the vehicle’s control arms and one inside the vehicle to collect vibration acceleration data for analysis. The Analysis of Variance (ANOVA) tests were performed to diagnose the effect of the vehicle-based sensors’ placement in the field. To classify road conditions and identify pavement distress (point of interest), the probability distribution was applied based on the magnitude values of vibration data.Findings Results from ANOVA indicate that pavement sensing patterns from the sensors placed on the front control arms were statistically significant, and there is no difference between the sensors placed on the same side of the vehicle (e.g., left or right side). A reference threshold (i.e., 1.7 g) was computed from the distribution fitting method to classify road conditions and identify the road distress based on the magnitude values that combine all acceleration along three axes. In addition, the pavement temperature was found to be highly correlated with the sensing patterns, which is noteworthy for future projects.Originality/value The paper investigates the effect of pavement sensors’ placement in assessing road conditions, emphasizing the implications for future road condition assessment projects. A threshold value for classifying road conditions was proposed and applied in class assignments (I-17 highway projects).

Thermodynamic analysis of pavement roads underground heat harvesting through water pipelines for effective management of urban heat island effect integrated to space cooling applications

Urban heat island effect drastically affects the climate by approximately increasing the surroundings temperature by 2°C, thus, rises the energy demand for space cooling. As roads/asphalt pavements makes 20–30% of urban areas that are fully exposed to solar radiations, this unused energy can be utilized by laying down a network of underground cross-linked polyethylene (PEX) pipes full of heat transfer fluids. In this research, the cold-water from a reservoir is pumped to various pipeline configurations to gain effective heat from the pavements/roads. This water circulation absorbs the heat, increasing the temperature (10–25°C) of cold water, also decreasing the pavement temperature by about 15°C. Furthermore, a solar collector is attached to increase temperature of circulated water to be used by low-grade temperature applications. Here, double effect absorption cooling (DEAC) and ejector cooling systems have been analysed thermodynamically for efficient space cooling application. The overall energy and exergy efficiency of DEAC integrated system is calculated to be 40.79% and 5.08%, respectively. The rate of cooling obtained by the evaporator is 6.75 kW, when rate of heat supplied is 4.3 kW. For the ejector cooling integrated system, the overall energy and exergy efficiencies are recorded as 15.27% and 3.38%, respectively. The rate of effective cooling through ejector cooling system is 2.7 kW.

Performance Comparison of Conventional and Biopolymer-modified Asphalt Mixtures for Airport Pavement

Raising the temperature of airport pavement softens its surface, leading to rutting or thermal cracking. As aircraft manufacturers lean toward heavier planes with higher tire pressures, challenges arise. To tackle these problems, incorporating polymers like high-density polyethylene into asphalt binders has emerged as a solution. This study investigates biopolymer-modified asphalt, blending conventional asphalt with highdensity polyethylene and pine resin. This study aims to compare the performance of asphalt mixtures using both conventional and biopolymer-modified asphalt binders. Various tests‒physical, Fourier transform infrared, energy dispersive X-ray, dynamic shear rheometer, volumetric properties, Marshall stability, retained stability, indirect tensile strength and Cantabro loss-were conducted. The results highlighted that integrating pine resin and high-density polyethylene increased the performance grade (PG) of the conventional asphalt from PG 64 to PG 82. Asphalt mixtures using biopolymer-modified binders exhibited superior stability, stiffness and resistance to moisture damage compared to those with conventional asphalt. These properties aligned with the specifications outlined in Item P-401 of the Federal Aviation Administration Advisory Circular 150/5370-10H. Keywords: Pine resin, High-density polyethylene, Biopolymer-modified asphalt, Performance grade 64, Performance grade 82

Multiscale finite element analysis of layer interface effects on cracking in semi-flexible pavements at different temperatures

This paper presents comprehensive research work on the crack initiation behavior of Semi Flexible Pavements (SFP) with the help of a one-way coupled multiscale modelling approach. The study focuses on elucidating the influence of layer interface conditions on potential cracking patterns under different temperature conditions. By integrating material properties at both local (mixture) and global (pavement) scales using a local de-homogenization approach, the interlocking effect was addressed within the asphalt binder's mesoscale properties. CT-image based mesostructure was employed to reconstruct the Representative Volume Element (RVE). Cohesive Zone Model (CZM) was utilized to simulate cracking initiation within the RVEs, with simulation results validated against practical engineering inspections. Additionally, a potential macroscopic failure index was introduced for SFP. It was found that the typical macroscopic failure indexes utilized for AC pavement may not be suitable for SFP due to the higher degree of heterogeneity. Analysis showed that SFP layer's coarse aggregate and cement grout at the bottom may experience compressive stress, while asphalt binder beneath the tire load may face high tensile stresses. Regardless of the interface conditions, top-down cracking was found to be the dominating failure mode in SFP. Besides, the vulnerable area in bonded interface SFP shifts from under tire load to the adjacent area with the rise in pavement temperature, while bottom-up cracking may appear only in unbonded interface SFP under low temperature conditions. Subsequent analysis demonstrated that top-down cracking is prominent in bonded interface SFP, especially at higher temperatures, compared to unbonded interface SFP. It is expected that critical observations for SFP highlighted above will certainly help in understanding critical failure modes and, hence, designing and constructing durable SFP structures.

Optimization of the installation techniques of distributed optic fiber sensors and measurement accuracy analysis for asphalt pavement based on finite element methods

The accurate measurement strain is critical to evaluating the structural integrity of asphalt pavements. The measurement strain error is caused by the encapsulation and installation of distributed optical fiber sensor (DOFS) for pavement monitoring. This study introduces an innovative approach to correct installation error. Firstly, a DOFS is embedded into asphalt pavement to simulate the mechanical response caused by traffic load. The optimal installation technology for each asphalt layer is proposed. In addition, the strain correction formula considering the pavement temperature is proposed for different asphalt layer. A rutting test is used to evaluate monitoring performance. Finally, a test road was built. A continuous temporal and spatial distribution strain of DOFS caused by traffic load is obtained. The results indicate that the average error rate of strain testing effectively decreases for each asphalt layer. In summary, this paper contributes to obtaining more accurate measurement strain of DOFS in pavement monitoring.

PREDICTION OF TEMPERATURE DISTRTBUTION INFLEXIBLE PAVEMENTS

In the present study, finite difference method is proposed to use for the development of Mathematical model for the prediction of the pavement temperature distribution (PPTD) in flexible pavement.To simpli$ the mathematical calculation, Visual Basic language was selected to perform a progam that has a capability fc.: the Prediction of Pavement Temperature as a function of depth and time. To test its accuracy, the program was applied to predict the pavement temperature distribution on specific location in section (R12) from the Expressway No.l in Iraq. The output of this program appears to be in good agreement with the (R12) observed data. Therefore the program can be recognized for use in the prediction of the asphaltic pavement temperature distribution

Development and performance verification of a water-retaining semi-flexible pavement material based on alkali-activated slag system incorporating superabsorbent polymers

Water-retaining semi-flexible pavement (WRSFP) can effectively mitigate the urban heat island (UHI) effect by reducing the pavement temperature through water evaporation. To reduce environmental impacts and enhance the water retaining capacity and mechanical properties of WRSFP, this paper investigated the effect of proportion of water-retaining grout (WRG) on workability of fresh WRG, compressive strength, flexural strength, and water absorption of hardened WRG based on alkali-activated slag (AAS) system. The optimal proportion of WRG was recommended. The microstructure of the hardened WRG was observed with a scanning electron microscope (SEM), which allowed for a better characterization and understanding of the degree of hydration and mechanical properties of WRG. The WRSFP specimens (WRSFP-20%, WRSFP-25% and WRSFP-30%) with different porosities of porous asphalt mixture (PAM) were tested for moisture susceptibility, rutting resistance and low-temperature cracking resistance. WRSFP-25% had the best moisture resistance and rutting resistance, and the worst low-temperature cracking resistance. The maximum difference of upper surface temperature between WRSFP and stone mastic asphalt (SMA), which is commonly used in pavement, was 13.3 °C. The time to reach 60 °C on the upper surface of WRSFP was 3.4 times longer than that of SMA, which showed an excellent cooling effect of WRSFP.

Influence of Deck Butt Weld Seams on Fatigue Life of Steel Bridge Decks Pavement: Parameter Optimization

Abstract The butt weld at the connection between orthotropic steel bridge decks (OSBDs) can potentially pose a hazard to the fatigue endurance of the steel bridge deck pavement. This study aims to optimize the parameters of the butt weld seam using finite element (FE) analysis. The optimized parameters will provide valuable guidance for the design of pavements with a focus on antifatigue properties. Initially, the dynamic modulus of the epoxy asphalt mixture (EAM) was determined through laboratory experimentation at various frequencies and temperatures. These material parameters were then used to compute the pavement’s fatigue life. Additionally, a well-established FE model was employed to analyze the deformation and fatigue life of the pavement structure. The validity of the model was verified by the theoretical calculation results. Various factors were considered, including vehicle velocities, pavement temperatures, and weld seam misalignments as well as weld seam dimensions such as height and width. The analysis was conducted using a three-dimensional steel bridge model. The results showed that decreasing pavement temperature, weld seam height, and misalignment led to an increase in pavement fatigue life. Conversely, reducing the weld seam width resulted in a decrease in fatigue life. Furthermore, the study investigated the coupling effect of different weld seam heights and widths on the fatigue life of the pavement. Contour figures were used to establish the parameter relationship formula for weld seam height and width. These findings are significant for pavement and deck designers because they enhance the understanding of the sensitivity of weld seams as design variables affecting the fatigue characteristics of pavement structures. Moreover, special attention should be given to the impact of welding parameters on the fatigue design of steel bridge deck pavement under high-temperature conditions of pavement structures.