Track buckling derailments present a challenge to the U.S. rail network. While track buckling is mostly associated with Continuously Welded Rail (CWR), it can also occur on jointed rail. In an attempt to prevent track buckling derailments, many railroads have adopted a precautionary procedure that involves issuing Slow Orders when daily ambient temperatures reach a certain level.

One side effect of this approach is excessive blanket slow orders and unnecessary heat inspections, which cost railways millions of dollars each year and have the potential to create congestion and bottlenecks.

The ENSCO Predicative Rail Temperature System will have a positive impact on safety and will minimize the impact on railroad operations by allowing for advance heat slow orders in an accurate, effective and targeted way.

ENSCO Rail Temperature Prediction Model – A More Accurate, Cost-effective Method

Predictive Rail Temperature Web application display
ENSCO's Predictive Rail Temperature Web Application Display

The ENSCO Rail Temperature Prediction Model replaces blanket slow orders with fewer, targeted heat slow orders and heat inspections. This translates to significant potential cost savings, increased overall train velocity, and fewer required resources.

The ENSCO Predicative Rail Temperature System predicts rail temperature more accurately than the current method, which is based on constant offset from ambient temperature. The ENSCO model uses the National Weather Service (NWS) data as weather forecast inputs and additional weather and material parameters, including:

  • Intensity of solar radiation
  • Solar angle
  • Wind speed
  • Sky temperature
  • Heat absorptivity and emissivity of rail

Key Technology Features

  • The model is based on heat transfer principles and calculates rail temperature based on the amount of energy absorbed from the sun and emitted via radiation and convection.
  • The predictions are granular; output is provided in 5.6 x 5.6 mile grids, which allow slow orders to be issued for specific milepost ranges. The model produces rail temperature prediction in 30-minute increments, and the predictions are updated every six hours.
  • The reports can be disseminated to both track maintenance management and field personnel via email or other methods to provide advance notice of probable rail temperatures that would trigger heat inspections and heat slow orders.

Cost and Operational Benefits

  • Advance warning for future slow orders is provided due to rail temperatures predicted 36-hours ahead.
  • Greater accuracy than the current approach with fewer, targeted heat slow orders and heat inspections because of fewer “target areas” as compared to blanket slow orders that cover a large territory. This can result in significant cost savings by translating to greater train velocity and fewer required resources.
  • Rail temperature forecasts are provided in 5.6 x 5.6 mile grids, which allow slow orders to be issued for specific milepost ranges.

Customized Reports

  • The Predictive Rail Temperature System includes access to a web application that allows users to display rail temperatures predicted 36 hours in advance, as well as a seven-day history for the entire continental U.S.
  • This information is also available as a report that can be custom-formatted and distributed via email or other means.

Additional Applications

  • Derailment investigation
  • Historical predicted rail temperature available as far back as 2010
  • Resource for development of CWR policies


Development of ENSCO Predictive Rail Temperature System was supported by Federal Railroad Administration, Office of Research Development and Technology.

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Ruben D. Peña B.

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Acacia Reber

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Bernhard Metzger

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ENSCO Rail, Inc., ENSCO Rail Australia Pty Ltd, ENSCO Technologies of Brazil LTDA/ENSCO Tecnologias do Brasil LTDA, and KLD Labs, Inc. are wholly owned subsidiaries of ENSCO, Inc. The ENSCO Rail subsidiaries provide the products and services to commercial customers.