History of changes to: Digital Twin for Predictive Corrosion Management towards Smarter Infrastructures
Date Action Change(s) User
Nov. 27, 2023, 2:13 p.m. Added 35 {"external_links": []}
Nov. 20, 2023, 2:03 p.m. Added 35 {"external_links": []}
Nov. 13, 2023, 1:33 p.m. Added 35 {"external_links": []}
Nov. 6, 2023, 1:31 p.m. Added 35 {"external_links": []}
Aug. 14, 2023, 1:31 p.m. Added 35 {"external_links": []}
Aug. 7, 2023, 1:32 p.m. Added 35 {"external_links": []}
July 31, 2023, 1:34 p.m. Added 35 {"external_links": []}
July 24, 2023, 1:35 p.m. Added 35 {"external_links": []}
July 17, 2023, 1:34 p.m. Added 35 {"external_links": []}
July 10, 2023, 1:26 p.m. Added 35 {"external_links": []}
July 3, 2023, 1:26 p.m. Added 35 {"external_links": []}
June 26, 2023, 1:26 p.m. Added 35 {"external_links": []}
June 19, 2023, 1:27 p.m. Added 35 {"external_links": []}
June 12, 2023, 1:29 p.m. Added 35 {"external_links": []}
June 5, 2023, 1:33 p.m. Added 35 {"external_links": []}
May 29, 2023, 1:27 p.m. Added 35 {"external_links": []}
May 22, 2023, 1:29 p.m. Added 35 {"external_links": []}
May 15, 2023, 1:31 p.m. Added 35 {"external_links": []}
May 8, 2023, 1:37 p.m. Added 35 {"external_links": []}
May 1, 2023, 1:28 p.m. Added 35 {"external_links": []}
April 24, 2023, 1:35 p.m. Added 35 {"external_links": []}
April 17, 2023, 1:28 p.m. Added 35 {"external_links": []}
April 10, 2023, 1:25 p.m. Added 35 {"external_links": []}
April 3, 2023, 1:26 p.m. Added 35 {"external_links": []}
Jan. 28, 2023, 11:08 a.m. Created 43 [{"model": "core.projectfund", "pk": 28243, "fields": {"project": 5446, "organisation": 4, "amount": 182615, "start_date": "2018-12-01", "end_date": "2019-11-30", "raw_data": 46742}}]
Jan. 28, 2023, 11:08 a.m. Created 40 [{"model": "core.projectperson", "pk": 54314, "fields": {"project": 5446, "person": 12771, "role": "PM_PER"}}]
Jan. 28, 2023, 10:52 a.m. Added 35 {"external_links": []}
April 11, 2022, 3:47 a.m. Created 43 [{"model": "core.projectfund", "pk": 20361, "fields": {"project": 5446, "organisation": 4, "amount": 182615, "start_date": "2018-12-01", "end_date": "2019-11-30", "raw_data": 25448}}]
April 11, 2022, 3:47 a.m. Created 41 [{"model": "core.projectorganisation", "pk": 77215, "fields": {"project": 5446, "organisation": 1365, "role": "PARTICIPANT_ORG"}}]
April 11, 2022, 3:47 a.m. Created 41 [{"model": "core.projectorganisation", "pk": 77214, "fields": {"project": 5446, "organisation": 6345, "role": "PARTICIPANT_ORG"}}]
April 11, 2022, 3:47 a.m. Created 41 [{"model": "core.projectorganisation", "pk": 77213, "fields": {"project": 5446, "organisation": 6345, "role": "LEAD_ORG"}}]
April 11, 2022, 3:47 a.m. Created 40 [{"model": "core.projectperson", "pk": 47613, "fields": {"project": 5446, "person": 6935, "role": "PM_PER"}}]
April 11, 2022, 1:48 a.m. Updated 35 {"title": ["", "Digital Twin for Predictive Corrosion Management towards Smarter Infrastructures"], "description": ["", "\nCorrosionRADAR Ltd (CR) and Sonomatic Ltd proposes a digital twin technology for predictive corrosion management of structures. Monitoring and predicting the corrosion and, specially, Corrosion Under Insulation (CUI), which can potentially cause catastrophic failures and/or major downtime for many sectors, are the main focus of the project consortium. CR technology strives to be a global leader in remote sensing technologies and advanced analytics systems for smart infrastructures. Most of the current practices of corrosion detection use a reactive approach, manual non-destructive techniques and risk management based on very limited data. CorrosionRADAR has developed a suite of IIOT (Industrial Internet of Things) enabled sensors which could detect and locate both moisture and corrosion under insulation. This proposal aims to extend sensor capability to include temperature measurement. A predictive digital twin of the structure will be created for CUI management. Prediction model, with machine learning capability, will be through a combination of knowledge base of field CUI data, analytical and data base from extensive laboratory testing. Digital twin allows the asset manager to visualise the state of structure and carry out what if analysis for future corrosion trajectory. Success of this project will pave the way for data driven predictive maintenance, reducing maintenance cost without compromising on the safety of people, assets and environment. This will also lead to reducing downtime and can equally be applied to many sectors such as oil & gas, renewables, food processing units, chemical and thermal power plants and nuclear.\n\n"], "extra_text": ["", "\n\n\n\n"], "status": ["", "Closed"]}
April 11, 2022, 1:48 a.m. Added 35 {"external_links": [20288]}
April 11, 2022, 1:48 a.m. Created 35 [{"model": "core.project", "pk": 5446, "fields": {"owner": null, "is_locked": false, "coped_id": "7d0759ee-eaa8-4f06-986b-41bb084222ed", "title": "", "description": "", "extra_text": "", "status": "", "start": null, "end": null, "raw_data": 25432, "created": "2022-04-11T01:40:54.440Z", "modified": "2022-04-11T01:40:54.440Z", "external_links": []}}]