Hindawi Publishing Corporation Modelling and Simulation in Engineering Volume 2012, Article ID 567864, 8 pages doi:10.1155/2012/567864 Research Article Turbulent and Transitional Modeling of Drag on Oceanographic Measurement Devices J. P. Abraham, 1 J. M. Gorman, 1 F. Reseghetti, 2 E. M. Sparrow, 3 and W. J. Minkowycz 4 1 School of Engineering, University of St. Thomas, 2115 Summit Aveune, St. Paul, MN 55105-1079, USA 2 ENEA, UTMAR-OSS, Forte S. Teresa, 19032 Pozzuolo di Lerici, Italy 3 Department of Mechanical Engineering, University of Minnesota, 111 Church Street SE, Minneapolis, MN 55455-0111, USA 4 Department of Mechanical and Industrial Engineering, University of Illinois at Chicago, Chicago, IL 60607, USA Correspondence should be addressed to J. P. Abraham, jpabraham@stthomas.edu Received 3 October 2011; Accepted 11 January 2012 Academic Editor: Guan Heng Yeoh Copyright © 2012 J. P. Abraham et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Computational fluid dynamic techniques have been applied to the determination of drag on oceanographic devices (expendable bathythermographs). Such devices, which are used to monitor changes in ocean heat content, provide information, that is, dependent on their drag coefficient. Inaccuracies in drag calculations can impact the estimation of ocean heating associated with global warming. Traditionally, ocean-heating information was based on experimental correlations which related the depth of the device to the fall time. The relation of time-depth is provided by a fall-rate equation (FRE). It is known that FRE depths are reasonably accurate for ocean environments that match the experiments from which the correlations were developed. For other situations, use of the FRE may lead to depth errors that preclude XBTs as accurate oceanographic devices. Here, a CFD approach has been taken which provides drag coefficients that are used to predict depths independent of an FRE. 1. Introduction Oceanography requires data samples of ocean information such as temperature and salinity at a sufficiently large num- ber of locations and times to ensure proper characterization of ocean properties. The creation of such data sets is con- strained by the number of measurements made around the globe. It is also constrained by the duration of measurement activities. For climate monitoring for instance, continuous measurements on the order of decades is required to extract a signal-to-noise ratio sufficient to make judgments about global warming Santer et al. [1]. One of the most commonly used devices for taking ocean temperature measurements is the expendable bathythermo- graph (XBT). Approximately 5 million XBT devices have been launched over the past few decades. XBT devices contain a temperature-sensing element housed within a streamlined object which is launched into the ocean. The XBT falls through the water at approximately 7 m/s. During its descent, a copper wire is unspooled maintaining an electrical connection with a data processing station onboard a ship. Temperature information is transmitted through the wire and is stored for processing. There are multiple varieties of XBT devices, each with a unique label. They are broadly separated into two classes (T4/T6/T7/T10/DB and the T5 class). The major difference between the two classes is the size of the XBT body. Additionally, there are two main XBT manufacturers (LM- Sippican and TSK). Slight differences in the manufacturing processes between these two suppliers and variations in the processes since the 1960s have introduced some variation in the fall rates of the respective devices [2–6]. Biases in XBT measurements have been known for approximately 40 years. These include biases in the estimated depth of the depth as well as biases in temperature. The biases have led to errors in ocean-heat estimations reported in [2, 7– 9]. Numerous efforts have been completed to reduce these biases and thereby increase the accuracy of oceanographic measurements made by XBT devices. These efforts have typically focused on improving the depth-time correlation of the FRE [10–13].