Wind farm construction requires large cranes to lift massive wind turbine structures over 300 feet tall and exceeding 160 tons. Installing these structures requires many crane “walks”, moving the heavy cranes around 50 miles along soil surfaces of varying strengths. Moving the cranes quickly is critical to installation economics, but this must be done safely by ensuring soil strength stability to avoid sinking or toppling the crane. Conventional best practices require cone penetrometer tests (CPTs) and performing numerical modeling to establish a safe path for moving the cranes requires on the order of four to six weeks. Itasca developed a rapid bearing capacity prediction tool using Python scripts, FLAC3D, and machine learning to provide near real-time feedback on the soil bearing capacity at a location, allowing enhanced crane walk planning.
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Dr. Chéng is a geomechanics engineer with academic background in numerical modeling and geotechnical engineering, and is a licensed Professional Engineer in California. He has research experience in the coupling of porous media and fluids, liquefaction models, and soil and rock mechanics.
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