BEGIN:VCALENDAR
VERSION:2.0
PRODID:-//Australian Tunnelling Society - ECPv6.16.3//NONSGML v1.0//EN
CALSCALE:GREGORIAN
METHOD:PUBLISH
X-ORIGINAL-URL:https://australiantunnellingsociety.com.au
X-WR-CALDESC:Events for Australian Tunnelling Society
REFRESH-INTERVAL;VALUE=DURATION:PT1H
X-Robots-Tag:noindex
X-PUBLISHED-TTL:PT1H
BEGIN:VTIMEZONE
TZID:Australia/Brisbane
BEGIN:STANDARD
TZOFFSETFROM:+1000
TZOFFSETTO:+1000
TZNAME:AEST
DTSTART:20230101T000000
END:STANDARD
END:VTIMEZONE
BEGIN:VEVENT
DTSTART;TZID=Australia/Brisbane:20240815T180000
DTEND;TZID=Australia/Brisbane:20240815T190000
DTSTAMP:20260620T233045
CREATED:20240805T022141Z
LAST-MODIFIED:20260209T013813Z
UID:19469-1723744800-1723748400@australiantunnellingsociety.com.au
SUMMARY:DAARWIN-GEMINI A novel tool to predict advance rate of a TBM in real-time
DESCRIPTION:Overview\nSAALG Geomechanics\, in collaboration with ACCIONA\, has developed DAARWIN-GEMINI\, a software system designed to optimize the performance of tunnel boring machines (TBMs) using machine learning-based techniques. The system key features include an advanced architecture for querying and processing data from the TBM database\, big data analysis and visualization in a web browser\, a ground-machine interaction model to predict the TBM advance rate and operation anomalies detection via machine learning algorithms to enhance the efficiency and reliability of tunnel excavation operations. The system has been validated in the Mularroya (Spain) hydraulic tunnel (small diameter shield TBM) in fractured rock mass with faulted and sheared zones\, and implemented in a larger diameter tunnel with EPB in Sao Paulo (Brazil) in weathered granite materials. In both cases\, the ground-machine excavation model was trained with excavation data from each tunnel and the model was deployed to provide real-time predictions of the penetration rate during the TBM operation. \nThis is an in-person and online event. \nLearning outcomes\nIn this presentation you will learn: \n\nHow machine learning is being applied within the tunnelling industry to improve productivity and reduce risk.\nA statistical approach to a ground-machine interaction model to predict the penetration rate of a TBM from performance parameters and geotechnical parameters.\nArchitecture and workflow of a system capable of providing predictions of the penetration rate at ring level and perform geotechnical back-analysis to assess spatial variability of ground parameters.\nLessons learned from the implementation of the system in two case studies\, a small diameter hydraulic tunnel in Spain and a metro tunnel in Brazil.\n\nEvent program\n\n5:30 pm AEST:  In-Person event registration opens\n6:00 pm AEST:  Event commences (online event starts here)\n7:00 pm AEST:  Event concludes\n\nAbout the speaker\n \nIgnasi Aliguer \nCTO and Co-Founder\, SAALG Geomechanics \nIgnasi Aliguer is Chief Technology Officer and Co-Founder at SAALG Geomechanics\, a software company and engineering firm focused on advanced digital tools for geotechnical engineering problems. Ignasi worked as a Research Engineer at Tech. University of Catalonia\, focusing on hydraulic fracture numerical simulations working with a major oil company. He also served as a Visiting Research Scholar at the University of Colorado at Boulder. He then joined Petrabytes\, a software company providing data solutions and visualization tools for the oilfield industry. Ignasi then co founded SAALG\, where he leads the team in charge of developing DAARWIN.
URL:https://australiantunnellingsociety.com.au/ats-event/daarwin-gemini-a-novel-tool-to-predict-advance-rate-of-a-tbm-in-real-time/
LOCATION:Online and in person at: Level 9\, 340 Adelaide Street\, Brisbane
CATEGORIES:Online,Queensland
END:VEVENT
END:VCALENDAR