CHAPTER 2

Findings

2.1 Introduction

In Pavement ME, environmental factors are considered using the EICM, a one-dimensional finite-difference program and sophisticated climatic modeling tool capable of simulating the flows of heat and moisture within a pavement structure. Based on the calculated heat and moisture flow, the EICM also models the corresponding changes in the behavior of pavement and subgrade materials. The EICM consists of three major components:

• The Climatic-Materials-Structural (CMS) model was developed at the University of Illinois (3). The original CMS model used the soil-moisture characteristics curve developed by Janssen and Dempsey (4). However, the original CMS model was later replaced by Gardner’s model (5) and then by the Soil-Water Characteristics Curve (SWCC) developed by Fredlund and Xing (6), which is currently implemented in the version of the EICM used by Pavement ME. The CMS model in the EICM was developed as a transient one-dimensional finite difference heat transfer model to predict the temperature in the asphalt layers. The required inputs for this model are thermal properties of materials, air temperature, solar radiation, and wind velocity. In this model, Fourier’s law was used for temperature prediction. The model has two boundary conditions: the surface temperature and the constant deep ground temperature node. At the upper boundary, the air temperature, wind speed, solar radiation, and pavement absorptivity and emissivity are used to determine the quantity of heat flowing into or out of the pavement. The lower boundary is a constant temperature capable of supplying an infinite amount of heat to maintain a constant temperature.
• The CRREL Frost Heave and Thaw Settlement model (hereafter the CRREL model) was developed at the United States Army Cold Regions Research and Engineering Laboratory (CRREL)(7). Although this model was implemented in EICM, it has never been used by Pavement ME. The boundary conditions for the CRREL model are based on the CMS outputs. The CRREL model is used to estimate the temperature within the subbase and subgrade layers by using the surface layer temperature profiles to compute the changes in the soil temperature profile. The model applies a finite difference solution to the governing water and temperature equations. Some of the required input variables are soil thermal conductivity, soil specific capacity, soil hydraulic conductivity, and the SWCC. The primary function or predicted outputs of the CRREL model relevant to the EICM are the frost and thaw depth calculations. The vertical heave due to frost formation and vertical settlement when the soil thaws is not used in the current EICM version. NCHRP Project 01-59, “Proposed Enhancements to Pavement ME Design: Improved Consideration of the Influence of Subgrade Soils Susceptible to Shrink/Swell and/or Frost Heave on Pavement Performance,” was recently completed and focused on improving the consideration and influence of subgrade soils susceptible to Shrink/Swell and/or Frost Heave on pavement performance.

• The Infiltration and Drainage (ID) model (8) and the Thornthwaite Moisture Index (TMI) model (9) were developed at Texas A&M University to estimate the moisture content within the unbound layers of a pavement structure. The current version of the EICM only uses the TMI model to estimate the moisture content in the unbound layers, which becomes an input to determine the soil suction using the SWCC curves. The current implemented version of the EICM in the Pavement ME design software uses the SWCC curves developed through the NCHRP Project 09-23, “Environmental Effects in Pavement Mix and Structural Design Systems” (10). The model uses the unbound and subgrade material inputs, such as the gradation, plasticity index (PI), and liquid limit, to calculate the various parameters needed to create the SWCC curves. The optimum moisture content is then used to obtain the equilibrium matric suction value for calculation purposes.

Since the initial development of the EICM, its various components have received many updates and changes, which are not well documented in the literature. Therefore, many of the detailed calculations for each model, as they are used in the EICM, are documented in Chapter 3.

2.2 Data Sources

Three different data sources have been used in Pavement ME, namely, physical weather stations [e.g., the National Climatic Data Center (NCDC) and others], NARR-assimilated data, and MERRA-assimilated data (includes MERRA and MERRA-2). The initial data source used in Pavement ME consists of physical weather stations that directly measure climatic conditions at a single point. These stations typically have the most representative data for a location but are expensive to construct and may not be near where a pavement is planned to be constructed. Many of these stations were located at airports. Additionally, the available hourly data varied greatly, and missing hourly values were common. As part of the original Pavement ME software, 1,083 physical weather stations were available for use. The majority (∼600) of these stations had climatic data ranging from 5 to 15 years. Many of these climate station files were updated to fill the gaps in the hourly values by using a linear interpolation between the maximum and minimum temperature for a given day. The physical weather stations will no longer be used in Pavement ME.

The NARR data source is primarily used for atmospheric research requiring historical atmospheric conditions and to study the variability of climate conditions. The NARR was developed by the National Centers for Environmental Predictions to model or assimilate observational data to produce a long-term overview of weather over North America. The model is initialized by using real-world temperature, winds, precipitation, and moisture conditions from the surface observations. The use of NARR hourly climate data in Pavement ME was addressed by Brink et al. (11), who found that a systematic bias did not exist between the NARR and NCDC ground-based observation data. It should be noted that the assimilated data did show some large differences for locations with large elevation differences over a short distance, typically found in mountainous locations. The NARR dataset that was incorporated in Pavement ME is being phased out and replaced by the MERRA-2 dataset. The MERRA-2 climate data were used during the global recalibration efforts completed for flexible pavements in 2018 and rigid pavements in 2021. In addition, the MERRA-2 climate data were the primary climate data source included in PMED version 3.0. The NARR data source will not be used or discussed further in this report.

The MERRA-2 data source utilized data from the EOS satellites to improve precipitation and water vapor climatology beginning in 1979 (2). FHWA and AASHTO have adopted its use and translated the variables into civil engineering applications, specifically pavement analysis and design. FHWA’s LTPP Climate Tool provides access to the MERRA-2 database for the variables listed in the report by Schwartz et al. (2) by generating site-specific climate data, based on the nearest available grid point, in a format compatible with Pavement ME. The climate inputs

available in the Climate Tool include temperature, precipitation, wind speed, percent sunshine, and relative humidity. AASHTOWare, in collaboration with FHWA and LTPP, developed and implemented a feature to directly select and download the MERRA-2 hourly climate data within the PMED application. The full MERRA-2 datasets available directly through NASA also include hourly solar radiation values based on measured actual cloud-cover fractions, which are not currently included in the LTPP InfoPave Climate Tool outputs used in Pavement ME. The solar radiation values are available for the LTPP sections and locations. Using MERRA-2 data can improve the accuracy and reliability of predicted pavement temperatures. Variations in the measurement of climatic attributes have also been reported to OWS. Using an assimilated dataset, such as MERRA-2, which spans the globe, can have significant benefits compared to individual weather stations across the United States. MERRA-2 data provide opportunities for enhancements to the climatic parameters and module calculations for pavement design using Pavement ME. They also provide improved climatology; higher frequency outputs, including hourly data; and additional locations beyond the United States. Table 1 compares some of the different features for each climate data source.

2.3 Identified Limitations

The EICM models and available data sources were investigated and reviewed to identify potential limitations that can be addressed with this research project. Several limitations that can be improved upon were identified. The identified improvements are related to the data sources used to characterize the local climate for a specific location, the limitations within the EICM itself, and the limitations in available documentation. The limitations addressed in this research project are summarized in the following sections.

2.3.1 MERRA-2 Data Limitations

• Assimilated data may not capture localized weather conditions.
• The spatial grid points may be further away from the pavement design project as desired.
• Obtaining the MERRA-2 data directly from NASA is tedious and requires significant personnel time (i.e., to set up the download scripts and coding knowledge) and machine time (i.e., to extract and process the data into a format compatible with the PMED software). However, most of the data are currently available through the LTPP Climate Tool. If any new variables are introduced, they would need to be downloaded and processed directly from NASA’s website, which can be time consuming.

• Currently, the MERRA-2 data implemented in the PMED are limited to the required inputs to the EICM climate model. These variables consist of air temperature, precipitation, percent sunshine, wind speed, and relative humidity. The MERRA-2 database has many more data elements that may be useful for pavement applications.

2.3.2 EICM Limitations

• Input Limitations
  • – The EICM input file and source code contain variables and methods not used in the analysis.
  • – Assuming that the mean annual air temperature (MAAT) is a reasonable starting point and using it as the constant deep ground temperature and initial nodal boundary condition causes issues in areas where the MAAT is below freezing.
  • – The EICM sets a predefined limit on the amount of convective heat transfer coefficient.
• Model Limitations
  • – The atmospheric energy balance model included in the EICM was derived using data from the Midwest United States and may not be applicable for another region. The model uses the air temperature and percent sunshine hourly values to estimate the shortwave and longwave radiation for a specific location.
• EICM Documentation
  • – Currently, a comprehensive stand-alone document detailing the contents of the EICM version embedded in the PMED does not exist, which is a major limitation that needs to be addressed. The EICM is a tool that can be used beyond pavement design, and clear documentation is essential. Documentation items to address include the following:
    • Inputs required for EICM,
    • Outputs generated by the EICM, and
    • Algorithms embedded in the EICM.