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Automated air-void system characterization of hardened concrete: Helping computers to count air-voids like people count air-voids---Methods for flatbed scanner calibration

Posted on:2009-07-10Degree:Ph.DType:Dissertation
University:Michigan Technological UniversityCandidate:Peterson, KarlFull Text:PDF
GTID:1442390002994409Subject:Engineering
Abstract/Summary:
Since the discovery in the late 1930s that air entrainment can improve the durability of concrete, it has been important for people to know the quantity, spacial distribution, and size distribution of the air-voids in their concrete mixes in order to ensure a durable final product. The task of air-void system characterization has fallen on the microscopist, who, according to a standard test method laid forth by the American Society of Testing and Materials, must meticulously count or measure about a thousand air-voids per sample as exposed on a cut and polished cross-section of concrete. The equipment used to perform this task has traditionally included a stereomicroscope, a mechanical stage, and a tally counter. Over the past 30 years, with the availability of computers and digital imaging, automated methods have been introduced to perform the same task, but using the same basic equipment. The method described here replaces the microscope and mechanical stage with an ordinary flatbed desktop scanner, and replaces the microscopist and tally counter with a personal computer; two pieces of equipment much more readily available than a microscope with a mechanical stage, and certainly easier to find than a person willing to sit for extended periods of time counting air-voids. Most laboratories that perform air-void system characterization typically have cabinets full of prepared samples with corresponding results from manual operators. Proponents of automated methods often take advantage of this fact by analyzing the same samples and comparing the results. A similar iterative approach is described here where scanned images collected from a significant number of samples are analyzed, the results compared to those of the manual operator, and the settings optimized to best approximate the results of the manual operator. The results of this calibration procedure are compared to an alternative calibration procedure based on the more rigorous digital image accuracy assessment methods employed primarily by the remote sensing/satellite imaging community.
Keywords/Search Tags:Air-void system characterization, Concrete, Methods, Air-voids, Automated, Count
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