GSA Annual Meeting in Phoenix, Arizona, USA - 2019

Paper No. 188-22
Presentation Time: 9:00 AM-6:30 PM

A-TTRACS: A GUI BASED APPLICATION FOR THE QUANTIFICATION OF AEOLIAN TURBULENCE AND TRANSPORT


TERESZKIEWICZ, Peter A., Naval Research Enterprise Internship Program, U.S. Naval Research Laboratory, 1005 Balch Road, Stennis Space Center, MS 39529; Department of Geography, University of South Carolina, Columbia, SC 29208, SWANN, Christy, U.S. Naval Research Lab,, Stennis Space Center, Stennis Space Center, MS 39529 and ELLIS, Jean T., Department of Geography, University of South Carolina, Columbia, SC 29208

Quantifying aeolian turbulence and sediment transport can be a cumbersome and computationally demanding process. In light of this hinderance, a new GUI-based computational suite has been developed within MATLAB app designer and Python to facilitate more rapid data processing. Aeolian Turbulence and Transport RApid Computational Suite (A-TTRACS) has the ability to process raw data from conventional field instrumentation including anemometry, saltation sensors, and moisture probes. Researchers are able to time average and filter input datasets and select from a variety of output parameters. A-TTRACS products include: shear velocity, mean wind speed, u’, v’, w’, Reynolds Stress, Turbulent Kinetic Energy (TKE), flow exuberance, moisture and saltation profile concentrations. An initial test run of the program computed 12 variables for a 30-minute field dataset sampled at 32 Hz (57,600 data points) within 12.6 seconds. A-TTRACS can also compute grain size statistics according to a variety of standardized measures (i.e., Folk and Ward (1957) modified geometric measures, Arithmetic, and Geometric method of moments). Post-processed datasets can be plotted immediately to visualize and assess data quality based on user input R-squared and p-value thresholds. The original and new dataset are combined into a single downloadable file for further analysis and application. A-TTRACS serves as a universal aeolian transport solver and operates within MATLAB and Python environments; making it accessible and applicable to a variety of aeolian research interests.