Richard L. Berg

Determining When to Place and Remove Spring Load Restrictions on Low-Volume Roads: Three Low-Cost Techniques

Damage to low-volume roads in seasonal frost areas can be kept to a minimum by implementing seasonal load restrictions (SLRs). However, not all agencies responsible for road management implement such restrictions, and among those that do, there is no standard technique. Some use qualitative methods, such as observation or dates. Others use quantitative methods, such as measuring or estimating stiffness or subsurface temperature. Loss and recovery of summertime pavement strengths can be directly measured with a falling-weight deflectometer (FWD). Alternatively, mathematical models of varying levels of complexity, using meteorological data, are in existence or are undergoing development for SLR placement. However, initial investment for an FWD can be prohibitive for agencies such as the U.S. Department of Agriculture Forest Service (FS), for which road management is not a primary mission. Similarly, such agencies have limited personnel to conduct detailed calculations required of complex mathematical models. Consequently, easy-to-use, low-cost alternatives are needed. In cooperation with other partnering agencies, FS has recently been evaluating several techniques for determining when to place and remove SLRs. Three methods that appear promising include (a) subsurface instrumentation for temperature and moisture, (b) portable or lightweight FWDs, and (c) the thaw index. Technology-and-development efforts in each of these areas are outlined here; field test programs, observations, and analysis procedures are discussed; and recommendations for implementing each method are provided.

Spring Thaw Predictor and Development of Real Time Spring Load Restrictions

In the fall of 2006, the State of New Hampshire Department of Transportation (NHDOT) began a two - year study to develop a Real Time Spring Load Restriction Methodology. The methodology is intended to guide the Maintenance Districts in their management of spring load restrictions by identifying the beginning and duration of spring thaw. Two methods will be used to determine how long load restrictions will be needed after the date of actual thaw: frost tube readings and computer model forecasting. A total of nine sites in the central part of the state were instrumented with frost tubes, water wells, subsurface temperature and moisture sensors, and weather stations. Falling Weight Deflectometer (FWD) tests were conducted at those sites from January 2008 through June 2008 with an additional test in August 2008 and another in October 2008. The U.S. Forest Service is continuing its work with the current developer of the Enhanced Integrated Climatic Model (EICM), which is embedded in the Mechanistic Pavement Design Procedure (MEPDG). It is proposed to use the EICM (isolated from the MEPDG) with the 7–10 day forecast temperatures to predict thaw. This paper describes the overall project, data collected to date, and preliminary results.

Calibration of a Freeze-Thaw Prediction Model for Spring Load Restriction Timing in Northern New England

A major problem with low-volume roads located in seasonal frost areas is their susceptibility to damage from trafficking during spring thaw. Therefore, seasonal load restriction (SLR) policies that limit the axle loads of heavy trucks during the spring thaw period have been implemented in many countries in an effort to minimize costly roadway damage. Several agencies have been addressing the question of when to place and remove SLRs and have expressed the need for a prediction model to aid them in the process of posting roads. Models are available which predict the depth of frost and thaw penetration based upon air freezing and thawing indices, requiring only air temperature data for input. Various forms of these models have been used by transportation agencies in the United States and Canada. When using any prediction model, a key element is model validation and calibration for local conditions. The purpose of the research described herein was to calibrate a freeze-thaw index model for use in SLR timing in northern New England. Atmospheric weather data and measured subsurface temperature data obtained from nine field test sites in New Hampshire over a period of three years were used in this analysis. Frost and thaw coefficients for the model were calibrated on a site-specific basis. Results suggest that frost-thaw patterns were reasonably estimated at most of the nine test sites using this model, although the model tended to be too conservative in estimating end-of-thaw dates, with estimated end-of-thaw dates falling after measured dates in many instances.

Keeping Springtime Low-Volume Road Damage to a Minimum: Toolkit of Practical Low-Cost Methods for Road Managers

There are approximately 3 million miles of low-volume roads (LVRs) in the United States, and approximately half of them are located in seasonal frost areas. Limiting or prohibiting loads during spring thaw can keep damage to a minimum. However, methods of determining when to place and remove spring load restrictions, particularly on LVRs, are often highly subjective—if restrictions are imposed at all. In partnership with several other agencies, the U.S. Department of Agriculture Forest Service has been compiling a toolkit of practical low-cost diagnostic techniques for determining conditions under which spring load restrictions should be placed and removed. This paper expands on techniques reported in a previous paper from a TRB low-volume roads conference and reports on further developments of additional methods. Techniques discussed include (a) subsurface instrumentation, (b) lightweight deflectometer, (c) thaw index, (d) climatic thaw predictor model, and (e) length of time. Requirements and equipment needed to use each of the techniques are described, strengths and weaknesses of each are outlined, and recommendations on various combinations of methods are provided to enable road managers to optimize placement of spring load restrictions.

Estimating When to Apply and Remove Spring Load Restrictions

A significant percentage of roads in seasonal frost areas are not designed to carry normal loads during the spring thawing process. Determining dates to apply and remove seasonal load restrictions (SLR) is of great interest to many federal, state and local agencies. In a recent study for the USDA Forest Service, Berg (2004) developed a method which estimated SLR application dates at a site in Minnesota and another in Ohio. In this report, we apply the same method to estimate SLR application dates on a road in New Hampshire and an airport parking apron in Vermont. The calculated results are compared to dates the SLR was actually applied and computed results were nearly the same as the application dates which were established by state DOT personnel. The method is also extended to estimate the time that the SLR can be removed. The Modified Berggren Equation was used to develop a procedure, but a regression equation developed by Rutherford, Mahoney, Hicks and Rwebingira (1985) was more accurate when compared to measured data.

Initial Analysis of the New Hampshire Spring Load Restriction Procedure

In late 2006, the New Hampshire Department of Transportation (NH DOT) initiated a study to develop a Real Time Spring Load Restriction (SLR) Methodology to guide the Maintenance Districts in their management of spring load restrictions by identifying the beginning and duration of the spring thaw period. The study includes selection of test areas, purchase and installation of instrumentation, collection and analysis of data from the instruments and development and implementation of the methodology, Eaton, et al (2009), discuss details of the project. In this paper the authors discuss the initial procedure, the installed instrumentation, observations from the instruments, and refinements indicated by the observations and initial analysis of the data.

Reducing damage to low-volume roads by using trucks with reduced tire pressures

Heavy-volume highways in seasonal frost areas are designed to resist the effects of spring thaw. However, timber access roads, county roads, and other low-volume roads with thin bituminous surfaces can be quite susceptible to pavement damage during midwinter- and spring-thaw periods. To reduce damage to low-volume roads, towns, cities, and states typically either post reductions in allowable load or completely prohibit hauling during damage-susceptible periods. Associated economic impact can be significant. To evaluate the effects of tire pressure on cumulative road damage, a mechanistic pavement design procedure developed by the U.S. Army Corps of Engineers for use in seasonal frost areas was used on a matrix of tire pressures, low-volume pavement cross sections, and environmental conditions. A series of computer simulations showed (a) trucks operating with conventional tire pressures can cause excessive damage, particularly in the form of cracking, to low-volume roads with thin bituminous surfaces during relatively short thaw periods; (b) pavement damage could be reduced substantially by restricting hauling to trucks operating with reduced tire pressures; and (c) there are “threshold” tire pressures under which only minimal damage occurs, even during critical spring thaw. These results could influence guidelines for hauling restrictions and, in turn, associated economics.

Preliminary Development of a Real Time Seasonal Load Restriction System for Remote Sites

By preventing the use of roadways by trucks with heavy axle loads, seasonal load restrictions (SLRs) minimize costly roadway damage that occurs in seasonal frost areas during the annual spring thaw and strength recovery period. Historically, load restrictions were often administered based on set dates and/or visual inspection procedures. More recently, however, many agencies have expressed the need for real time monitoring of subsurface temperature and moisture regimes to assist them in making SLR decisions. Gathering this data may be problematic, however, because many roadways requiring SLRs are located in remote areas where it is difficult to gather these data in real time. Therefore, this research projects main focus is to demonstrate the application of commercial remote sensing and spatial information (CRS&SI) technology for monitoring roadway conditions in real time during the spring thaw and strength recovery period. Test sites will be established in northern New England that will include sensors for measuring subsurface temperature and moisture regimes, as well as above ground sensors to monitor several atmospheric weather parameters. Data will then be transferred (via satellite) to a web based Decision Support System (DSS), which will consist of a graphical user interface (GUI), a database, interpolation and other data processing tools, and a freeze-thaw predictive model. Weather forecasts will be automatically downloaded and entered into the predictive model to assist transportation agencies in making SLR posting decisions several days in advance.

Can Spring Load Restrictions on Low-Volume Roads Be Shortened Without Increasing Road Damage?

Major highways are designed to withstand heavy vehicles and high volumes of traffic year round. However, low-volume roads in seasonal frost areas are highly susceptible to damage from trafficking by heavy vehicles during spring thaw. Conventional practice is to place partial or full spring load restrictions on low-volume roads during spring thaw. This practice reduces road damage significantly. However, companies whose livelihood depends on trucking can suffer major economic losses as they await the removal of load restrictions. Using reduced tire pressure constitutes a less conventional technique that can reduce springtime damage. Reducing tire pressure generally appears to be less effective than reducing load. Nevertheless, it does appear that the load restriction window can be shortened in duration by implementing a reduction in tire pressure for a few weeks, starting toward the latter part of the standard spring load restriction period. With a mechanistic pavement design and evaluation model for seasonal frost areas, a critical combination of load and tire pressure reduction was developed; it contributes to optimizing the balance between minimizing springtime road damage and minimizing disruption to local economies caused by load restrictions. This analysis constitutes the first step in the development of simplified, general application guidelines for shortening the springtime load restriction window for a variety of pavement structures.

Modification of the U.S. Army Corps of Engineers Model 158 for Prediction of Frost–Thaw Profiles in Northern New England

Knowledge concerning frost–thaw profiles is important in the design of pavements for low-volume roads located in seasonal frost areas. In addition, because these roads are highly susceptible to damage during the spring thaw–weakened period, this knowledge is helpful in making decisions about seasonal load restriction (SLR) policies. Direct measurement of frost depth is expensive and usually limited in scope. Therefore, several highway agencies have expressed the need for a prediction model to help them in estimating frost–thaw profiles beneath roadways. A report from the U.S. Army Corps of Engineers New England Division examined frost prediction models. One of the equations in that report was Model 158, which was similar to the modified Berggren equation. Model 158 uses air temperature indexes as well as pavement material properties to integrate heat flow into the calculation of maximum seasonal frost depth. That model has been modified slightly and programmed in an Excel spreadsheet to predict frost and thaw depths on a daily basis. This paper presents an overview of the modified Model 158 and compares predictions obtained from that model with measured frost–thaw profiles obtained at several test sites located in northern New England during a period of five freeze–thaw seasons. Results suggest that the model shows much promise although it generally tended to slightly underpredict maximum frost depths. In tracking the thaw process for SLR posting, the model tended to be conservative in estimating end-of-thaw dates (especially during rapid thawing events); in many instances, estimated end-of-thaw dates fell after measured dates.